{"id":"W4292790999","doi":"10.1111/2041-210x.13955","title":"The power of forecasts to advance ecological theory","year":2022,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Division of Graduate Education; Institute for Critical Technology and Applied Science; Ministry of Business, Innovation and Employment; Royal Society Te Apārangi; National Oceanic and Atmospheric Administration; Tertiary Education Commission; Nuclear Safety and Security Commission; Alfred P. Sloan Foundation; Division of Environmental Biology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Generality; Predictability; Ecological systems theory; Ecology; Relevance (law); Computer science; Management science; Engineering; Economics; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01251529,0.0007141757,0.0005945493,0.002362496,0.0009785392,0.004314748,0.00117548,0.001476256,0.006108999],"category_scores_gemma":[0.07846184,0.0004037195,0.0007283933,0.001576873,0.004046205,0.008356608,0.002492177,0.003008393,0.0007098101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002068105,"about_ca_system_score_gemma":0.001715747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005564569,"about_ca_topic_score_gemma":0.002952655,"domain_scores_codex":[0.9963474,0.002302602,0.0001671933,0.0004333897,0.00060415,0.0001451774],"domain_scores_gemma":[0.9280461,0.05959341,0.003473584,0.00448366,0.003528107,0.0008750709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002123153,0.00005809651,0.01505214,0.0002722748,0.0001145439,0.0001073824,0.001232066,0.1201551,0.0006011638,0.7402712,0.008730743,0.113193],"study_design_scores_gemma":[0.00002554315,0.00003739748,0.002680294,0.0001970599,0.00002440049,0.00002846418,0.0003354845,0.1679804,0.000358837,0.8185222,0.009765564,0.00004432239],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1531154,0.005793133,0.6717469,0.05389762,0.002263631,0.0001068892,0.001338068,0.001269047,0.1104694],"genre_scores_gemma":[0.9379419,0.00183905,0.0566008,0.0007398853,0.0006009798,0.0000593973,0.0003032741,0.0001161506,0.001798606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01251529,"threshold_uncertainty_score":0.06618798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347939872089398,"score_gpt":0.3317719384428491,"score_spread":0.3082925397219551,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}