{"id":"W2586879642","doi":"10.1080/10304312.2017.1275078","title":"Fit or fitting in: deciding against normal when reproducing the future","year":2017,"lang":"en","type":"article","venue":"Continuum","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Medical Research Council; National Health and Medical Research Council","keywords":"Normative; Judgement; Prejudice (legal term); Standard deviation; Diversity (politics); Reproduction; Norm (philosophy); Term (time); Multitude; Gamete; Value (mathematics); Psychology; Social psychology; Sociology; Epistemology; Law; Statistics; Political science; Mathematics; Medicine; Philosophy; Biology","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":[0.02279026,0.0003656155,0.0004020053,0.0008513052,0.008186438,0.006808877,0.001298671,0.004250373,0.003365576],"category_scores_gemma":[0.04702446,0.0003450796,0.000422178,0.0004750639,0.03667221,0.008540073,0.005858836,0.005844397,0.0006404824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003392791,"about_ca_system_score_gemma":0.006234392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005259892,"about_ca_topic_score_gemma":0.0063877,"domain_scores_codex":[0.9762641,0.01788097,0.0006969665,0.001091797,0.002280342,0.001785762],"domain_scores_gemma":[0.9894297,0.005528194,0.00133583,0.001093551,0.001319449,0.001293326],"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":[0.00007964703,0.00009294284,0.0113334,0.00009489489,0.0000176831,0.002054402,0.4043886,0.0003607578,0.002663068,0.5336969,0.009319864,0.03589786],"study_design_scores_gemma":[0.0000279847,0.0002065248,0.006838238,0.00064878,0.00003018345,0.003655653,0.4665409,0.001464719,0.00244108,0.3271612,0.1908325,0.0001521807],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5143721,0.002328334,0.07050458,0.1546227,0.001809397,0.0003523912,0.00008129157,0.0001618629,0.2557673],"genre_scores_gemma":[0.9831549,0.0003719825,0.006890784,0.005068998,0.00007650058,0.00006570017,0.00001859757,0.00003483092,0.004317733],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02279026,"threshold_uncertainty_score":0.1205279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05810866449130941,"score_gpt":0.3410879866710275,"score_spread":0.2829793221797181,"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."}}