{"id":"W3167141676","doi":"10.32920/ryerson.14665533.v1","title":"Environmental Management in the Film and Television Production Industry","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McGill University","funders":"","keywords":"SWOT analysis; Business; Production (economics); Competitive advantage; Marketing; Environmental resource management; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001969521,0.000141242,0.0001125202,0.001463318,0.003160626,0.004228512,0.0004175768,0.0009349568,0.003459768],"category_scores_gemma":[0.003410748,0.0001295341,0.000103819,0.002319015,0.002132726,0.001863166,0.001575245,0.0007965516,0.0002641779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002617313,"about_ca_system_score_gemma":0.002830538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009707348,"about_ca_topic_score_gemma":0.01550055,"domain_scores_codex":[0.9980202,0.0008160418,0.00006767847,0.0001623291,0.0005520087,0.0003817099],"domain_scores_gemma":[0.9974521,0.001249097,0.0004996264,0.00008144118,0.000417799,0.0002999191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002332313,0.001042276,0.1733713,0.001231918,0.00005887588,0.005555279,0.182749,0.001881603,0.01288037,0.06223684,0.01237828,0.5463809],"study_design_scores_gemma":[0.0000176194,0.0004851068,0.3221571,0.00064521,0.00003974328,0.00112194,0.3827787,0.001648312,0.007266607,0.006056496,0.277708,0.00007525669],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8666679,0.005011989,0.0009884827,0.005032942,0.00007392691,0.00003042737,0.0000230898,0.00001891142,0.1221523],"genre_scores_gemma":[0.9886919,0.003002706,0.0004642103,0.0002579933,0.00003763934,0.000007984742,0.00002121757,0.000005665709,0.007510697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009707348,"threshold_uncertainty_score":0.01930171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113996770171516,"score_gpt":0.2121414971306356,"score_spread":0.2010015294289205,"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."}}