{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005232003,0.0001569047,0.0005041604,0.0002255359,0.0003195204,0.0001268767,0.0006705679,0.0003331653,0.0005271224],"category_scores_gemma":[0.0004390414,0.0003365556,0.0001600626,0.0008029447,0.0002492195,0.0003205398,0.0003628616,0.0006768459,0.0004650608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006484757,"about_ca_system_score_gemma":0.0002004732,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03111334,"about_ca_topic_score_gemma":0.07202695,"domain_scores_codex":[0.9983733,0.00004737922,0.0003918041,0.0005009436,0.00007423342,0.0006123593],"domain_scores_gemma":[0.9985905,0.0001479425,0.0002483664,0.0004402061,0.00007169797,0.0005012946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002393077,0.00006324131,0.7432659,0.0000173847,0.00007879764,0.00007303947,0.0006847598,0.00001328457,0.0000118195,0.01052949,0.2441521,0.001086263],"study_design_scores_gemma":[0.001669267,0.0001050714,0.08619861,0.00002709925,0.00004008745,0.00001405945,0.001657315,0.0002641986,0.00000407394,0.0189846,0.8905831,0.0004525211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6872848,0.001948523,0.0005208633,0.001654771,0.0008476577,0.0004169386,0.0001843628,0.0002384772,0.3069036],"genre_scores_gemma":[0.8522046,0.0004807228,0.0003404891,0.0002809368,0.0001805437,0.000005533388,0.00001625755,0.00003169426,0.1464592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6570672,"threshold_uncertainty_score":0.9999086,"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."}}