{"id":"W2540442197","doi":"10.1177/0162243916671201","title":"The Truthiness about Hurricane Catastrophe Models","year":2016,"lang":"en","type":"article","venue":"Science Technology & Human Values","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Theoretical Astrophysics","keywords":"Stylized fact; Context (archaeology); Actuarial science; Risk management; Economics; Scarcity; Appeal; Risk analysis (engineering); Business; Political science; Law; Microeconomics; Finance; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0005028399,0.0001523838,0.0001637102,0.000302997,0.002784011,0.0001557781,0.002003125,0.0001020941,0.0004723783],"category_scores_gemma":[0.0002324129,0.00006608897,0.00005217638,0.001462733,0.01087457,0.000473345,0.0001249282,0.0002388374,0.0004426966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001791688,"about_ca_system_score_gemma":0.0001136551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005713544,"about_ca_topic_score_gemma":0.0008537284,"domain_scores_codex":[0.9975876,0.00005045814,0.0002443153,0.0005219206,0.0006759282,0.0009197295],"domain_scores_gemma":[0.9988766,0.0001703857,0.00006112712,0.0006051849,0.0001327268,0.0001540291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002808198,0.00002774375,0.2020641,0.000004912384,0.00001096058,0.00002129549,0.0000638147,0.00009759451,0.01270997,0.1516581,0.0003387312,0.6329747],"study_design_scores_gemma":[0.0003177401,0.0003620434,0.449791,0.00002595928,0.000007025395,0.0000270938,0.0002347252,0.0009456126,0.00264168,0.5390694,0.006322208,0.0002555689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881407,0.0009149708,0.000641412,0.005892611,0.0002274912,0.0001493886,0.000020646,0.0002558064,0.003756964],"genre_scores_gemma":[0.9987046,0.000117052,0.0003479082,0.00005329624,0.00006683725,0.000005729197,0.000001956157,0.000003335058,0.000699279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6327192,"threshold_uncertainty_score":0.9985142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02059301512935777,"score_gpt":0.2725414362093229,"score_spread":0.2519484210799651,"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."}}