{"id":"W6921709820","doi":"10.7916/d8-awcv-3e60","title":"Marie de Kerstrat","year":2015,"lang":"en","type":"article","venue":"Columbia Academic Commons (Columbia University)","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compromise; Negotiation; Movie theater; Field (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008683164,0.0004249723,0.0002281005,0.0007929388,0.003061268,0.004727126,0.0005958172,0.001546858,0.08366538],"category_scores_gemma":[0.005689451,0.0003348489,0.0001459121,0.0005099163,0.001171471,0.002362037,0.001658348,0.001702843,0.02395382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003966797,"about_ca_system_score_gemma":0.004091439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05145603,"about_ca_topic_score_gemma":0.09704361,"domain_scores_codex":[0.9986571,0.0002400641,0.000032426,0.0003485876,0.0005329922,0.0001888349],"domain_scores_gemma":[0.9978653,0.0004129668,0.0001669778,0.00008786665,0.0008436447,0.0006232822],"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":[0.00005380097,0.00003068798,0.001535101,0.0001857273,0.000006818377,0.0004673027,0.004494436,0.00008243602,0.001285444,0.0383118,0.8856926,0.06785382],"study_design_scores_gemma":[0.000001372787,0.00000425621,0.0004931258,0.00007256575,0.000001094745,0.0002274885,0.0008248354,0.00002281049,0.0001429686,0.0004105557,0.9977927,0.000006085401],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01872305,0.04900533,0.002327601,0.1500899,0.01305282,0.00008958982,0.0009290161,0.000422305,0.7653604],"genre_scores_gemma":[0.08307123,0.01261625,0.0008599655,0.01243167,0.00111491,0.0000425349,0.0001521401,0.0002480323,0.8894632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08366538,"threshold_uncertainty_score":0.2798886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05644159720562175,"score_gpt":0.2123919147298228,"score_spread":0.1559503175242011,"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."}}