{"id":"W2494685530","doi":"10.7228/manchester/9780719099458.003.0005","title":"New selection grids: points tests and gender effects, 1993–2003","year":2016,"lang":"en","type":"book-chapter","venue":"Manchester University Press eBooks","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Computer science; Econometrics; Mathematics; Artificial intelligence","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":[0.005850898,0.000148632,0.0003051199,0.001884474,0.0007330893,0.001275964,0.001002757,0.0003700948,0.01484266],"category_scores_gemma":[0.02261162,0.0002026576,0.0002784113,0.007335291,0.001026702,0.001067408,0.001005394,0.001125944,0.001457248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004316323,"about_ca_system_score_gemma":0.003066743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4626687,"about_ca_topic_score_gemma":0.5535964,"domain_scores_codex":[0.9970747,0.0008634703,0.0001260918,0.0001976772,0.001490101,0.0002478172],"domain_scores_gemma":[0.9836996,0.008831501,0.002230505,0.0008805278,0.003750682,0.0006072447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000465771,0.0001166681,0.3691054,0.0002282049,0.0001079323,0.000309951,0.009205688,0.005898396,0.0002203678,0.04372113,0.2135106,0.3571099],"study_design_scores_gemma":[0.00002696229,0.00006749921,0.828622,0.0002021672,0.00004138163,0.00008246447,0.004282438,0.002736224,0.0003267526,0.004836421,0.1587422,0.00003344514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6625875,0.01314795,0.009476732,0.01834101,0.0007787752,0.000223336,0.04977751,0.0004605377,0.2452066],"genre_scores_gemma":[0.9127208,0.003683011,0.00376243,0.0006114562,0.000243597,0.0001212567,0.01601681,0.0002035348,0.06263702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4626687,"threshold_uncertainty_score":0.9199514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03836702713978242,"score_gpt":0.1852191762136699,"score_spread":0.1468521490738874,"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."}}