{"id":"W2561746565","doi":"","title":"WXN Presents Prof. Poonam Puri: The Pipeline Problem: Board Diversity in Canada","year":2016,"lang":"en","type":"article","venue":"","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Diversity (politics); Political science; Computer science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0001252234,0.0001043072,0.0001174598,0.00005399383,0.0001438199,0.00004130982,0.0003184686,0.00002153306,0.0005648337],"category_scores_gemma":[0.000008202223,0.00005546636,0.00003090402,0.0001045346,0.00003300846,0.0005452358,0.0002484947,0.00004950227,0.0001432926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001036314,"about_ca_system_score_gemma":0.00008307739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9735196,"about_ca_topic_score_gemma":0.9887757,"domain_scores_codex":[0.9992492,0.000002877644,0.0001761479,0.0001573644,0.0001202603,0.0002941375],"domain_scores_gemma":[0.9997157,0.00001917894,0.00006589156,0.0001626938,0.00002570645,0.00001075937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001214129,0.00001611175,0.9050782,0.00002272457,0.000008008801,0.000003199849,0.00002659628,0.00001227989,0.000018503,0.002279635,0.09052744,0.001995209],"study_design_scores_gemma":[0.0005930785,0.000001316292,0.7404684,0.00002382281,0.00001395282,2.356978e-7,0.0001584684,0.0001614548,0.00002970251,0.0018329,0.2565556,0.0001610525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8955764,0.00001937373,0.00003853713,0.02618382,0.0002611784,0.0003314101,0.000007157717,0.0000493816,0.07753277],"genre_scores_gemma":[0.9862604,0.000008537281,0.000008945659,0.002162735,0.0002798776,0.00001038337,0.000004271202,0.000007804573,0.01125709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1660282,"threshold_uncertainty_score":0.6184533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01909105464244422,"score_gpt":0.1767648552684859,"score_spread":0.1576738006260417,"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."}}