{"id":"W3024074409","doi":"","title":"Assessing the Approximate Validity of Moment Restrictions","year":2015,"lang":"en","type":"preprint","venue":"Toulouse Capitole Publications (University Toulouse 1 Capitole)","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Agence Nationale de la Recherche","keywords":"Divergence (linguistics); Moment (physics); Measure (data warehouse); Invariant (physics); Econometrics; Mathematics; Statistical hypothesis testing; Set (abstract data type); Computer science; Statistics; Data mining","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001670607,0.0007085057,0.0008397156,0.001765529,0.001268182,0.001514551,0.002412692,0.0005619802,0.0004821478],"category_scores_gemma":[0.0003103452,0.000714989,0.0005319736,0.002343964,0.0004649847,0.0026909,0.00330833,0.001399337,0.0001592179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005213789,"about_ca_system_score_gemma":0.0008420199,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006976436,"about_ca_topic_score_gemma":0.0006303189,"domain_scores_codex":[0.9960178,0.0002293012,0.000809405,0.001135227,0.001038198,0.0007700485],"domain_scores_gemma":[0.9933906,0.0002688703,0.001558617,0.002647332,0.002004714,0.0001299239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002882556,0.005386886,0.1687215,0.004157763,0.001884553,0.0001660771,0.008368667,0.007230985,0.00122671,0.125404,0.618749,0.05841553],"study_design_scores_gemma":[0.003139597,0.00005131774,0.1507835,0.0006327509,0.004961737,0.00004776251,0.02338856,0.03038641,0.0001620938,0.01226672,0.7704791,0.003700476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9449799,0.0005121616,0.00638414,0.009160022,0.002337552,0.0020185,0.0002599314,0.0010863,0.03326146],"genre_scores_gemma":[0.9926599,0.000283735,0.001060201,0.0002995123,0.001236408,0.00007498443,0.0008957642,0.0001409124,0.00334862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1517301,"threshold_uncertainty_score":0.9996362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0803043938128028,"score_gpt":0.281048431129284,"score_spread":0.2007440373164812,"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."}}