{"id":"W1508040273","doi":"","title":"Explanation and Misrepresentation in the Laboratory","year":2006,"lang":"en","type":"preprint","venue":"Digital Archive @ GSU","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Iowa State University; University of Alberta; Lehigh University","keywords":"Misrepresentation; Incentive; Predictability; Value (mathematics); Actuarial science; Economics; Microeconomics; Computer science; Statistics; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001857768,0.0001104615,0.0001227031,0.00007523842,0.0001600599,0.0003618373,0.000198701,0.00005570069,0.000003818969],"category_scores_gemma":[0.00005373911,0.00009818438,0.00003578264,0.00006267681,0.0003062378,0.0002492706,0.0002154909,0.0001770797,0.0000121855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008647206,"about_ca_system_score_gemma":0.00006280439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004632519,"about_ca_topic_score_gemma":0.004888763,"domain_scores_codex":[0.999153,0.0001016739,0.0001774925,0.0002518088,0.0001637685,0.0001522534],"domain_scores_gemma":[0.9995949,0.0001395619,0.00009369859,0.0001222597,0.00002195594,0.00002757988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000447297,0.0004401279,0.6373942,0.00006283426,0.00004646895,0.00004504614,0.2435519,0.0001435727,0.000233731,0.06293853,0.01730045,0.0377984],"study_design_scores_gemma":[0.0007410288,0.00007698627,0.6697651,0.000146328,0.00003440236,0.000001529414,0.05865844,0.0001724574,0.000249442,0.2413893,0.02779772,0.0009673157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8335134,0.0002825569,0.00002704938,0.0009519655,0.0001596238,0.0004141253,0.0003318051,0.00002640997,0.1642931],"genre_scores_gemma":[0.999085,0.00007392974,0.0000803722,0.00009465835,0.0001191845,0.00009189585,0.0002740493,0.000007505383,0.0001734014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1848935,"threshold_uncertainty_score":0.7003013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0294576730208357,"score_gpt":0.3268772199227506,"score_spread":0.2974195469019149,"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."}}