{"id":"W4245305366","doi":"10.1177/0197918318781832","title":"Selections Before the Selection","year":2018,"lang":"en","type":"article","venue":"International Migration Review","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"Selection (genetic algorithm); Geography; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005579744,0.00006535376,0.00006876551,0.00004704395,0.0006213079,0.00009515003,0.0002278955,0.00004004027,0.003068807],"category_scores_gemma":[0.0003924447,0.00004732612,0.00006564484,0.000502681,0.0001420076,0.000220024,0.00001190653,0.00009035422,0.0004018361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001152618,"about_ca_system_score_gemma":0.0001098103,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008830387,"about_ca_topic_score_gemma":0.1958751,"domain_scores_codex":[0.9990404,0.000157867,0.000210544,0.0001282548,0.0003506471,0.0001123103],"domain_scores_gemma":[0.9990301,0.00003312134,0.0001095293,0.00008984441,0.0006954981,0.00004194074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005821786,0.00007463484,0.006090515,0.00003834113,0.00007081327,3.446413e-7,0.009615991,0.00001726089,0.0000828154,0.5450578,0.3519841,0.08696159],"study_design_scores_gemma":[0.00003494514,0.0000200619,0.001366142,0.0001074462,0.00001569045,0.000003083938,0.0002472568,0.001674414,0.00001139046,0.0007308581,0.9957405,0.00004820209],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04645841,0.007582438,0.02471913,0.6553691,0.006370655,0.002478578,0.00004727564,0.0007219496,0.2562525],"genre_scores_gemma":[0.8656487,0.03816172,0.0009725773,0.02387611,0.004638561,0.0002257784,0.0001213672,0.00002293278,0.0663323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8191903,"threshold_uncertainty_score":0.9978426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792405888168777,"score_gpt":0.3571606487877896,"score_spread":0.3392365899061018,"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."}}