Scientific Method for Geoscience Research

When to Use This Skill

Invoke when:

Formulating or testing hypotheses
Designing validation experiments
Evaluating strength of evidence
Deciding if a finding is confirmed vs preliminary
Setting up controls and reproducibility checks

Core Principles

1. Evidence Hierarchy

Apply this hierarchy when evaluating claims:

| Level | Description | Example | |-------|-------------|---------| | Tier 1 | Multi-proxy validation | δ18O + Mg/Ca + δ13C all show signal | | Tier 2 | Two independent lines | δ18O + historical documentation | | Tier 3 | Single proxy | Only δ18O shows anomaly |

2. Verification Standards

Minimum for confident claims:

One source = coincidence (interesting but unverified)
Two sources = clue (worth investigating)
Three sources = verified (minimum for publication)

3. Hypothesis Formulation

Good hypotheses are:

Falsifiable: Define what evidence would disprove it
Specific: Include testable predictions with measurable outcomes
Bounded: State assumptions and limitations upfront

Template:

HYPOTHESIS: [Claim]
PREDICTION: If true, we should observe [specific outcome]
FALSIFICATION: If we observe [contrary evidence], hypothesis is rejected
ASSUMPTIONS: [List key assumptions]

4. Controls and Reproducibility

For each analysis, identify:

Positive controls: Known events that SHOULD be detected
Negative controls: Periods that SHOULD NOT show signal
Blind tests: Analyze data without knowing expected result first

5. Uncertainty Language

Use precise language:

| Term | Meaning | When to Use | |------|---------|-------------| | "proposed" | Unconfirmed hypothesis | Single line of evidence | | "likely" | Probable (2+ sources) | Two independent confirmations | | "confirmed" | Multi-proxy validated | Three+ independent lines | | "suggests" | Indicates direction | Preliminary interpretation | | "consistent with" | Doesn't contradict | Supportive but not proof |

NEVER use: "100%", "definitely", "certainly", "must be", "proves"

6. Red Flags

Stop and reconsider if:

[ ] Finding seems too clean/perfect
[ ] No alternative explanations considered
[ ] Post-hoc selection of "successful" cases
[ ] Confirmation bias (looking for expected result)
[ ] Circular reasoning (using conclusion as premise)

7. Breakthrough Skepticism

When you think you've made a major discovery:

Pause - Don't immediately declare success
Check arithmetic - Verify calculations independently
Seek alternatives - What else could explain this?
Consult literature - Has this been tried before?
Sleep on it - Fresh eyes often find flaws

Workflow for New Hypothesis

1. STATE the hypothesis clearly
2. DEFINE falsification criteria
3. IDENTIFY positive/negative controls
4. GATHER data (ideally blind to expected result)
5. ANALYZE using pre-defined methods
6. EVALUATE against falsification criteria
7. DOCUMENT regardless of outcome
8. REPORT uncertainty honestly

Example: Testing Earthquake Detection

Hypothesis: Speleothem δ18O detects M6+ earthquakes within 50 km

Prediction: Known historical earthquakes should show z > 2.0 anomalies within ±10 years of event

Falsification: If >50% of known earthquakes show no anomaly, hypothesis is rejected

Positive controls: 1896 Independence M6.3 (48 km from Crystal Cave)

Negative controls: Periods with no documented seismicity

Test result: 6/6 positive controls detected → Tier 2 evidence (small n, needs replication)