{"id":"W2901919771","doi":"10.1080/19396368.2018.1532556","title":"Special Issue in Honor of Gordon H. Dixon","year":2018,"lang":"en","type":"article","venue":"Systems Biology in Reproductive Medicine","topic":"Birth, Development, and Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Honor; Reproductive biology; Biology; Classics; Philosophy; Computer science; Art; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.002123719,0.0002005457,0.001014409,0.0005433346,0.00003370828,0.000001161867,0.00011837,0.0002291976,0.000272909],"category_scores_gemma":[0.0009928998,0.0001428217,0.00002983951,0.0006506223,0.0009082637,0.00003606559,0.00004367909,0.0003354764,0.00007106438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002215849,"about_ca_system_score_gemma":0.0002216117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002815722,"about_ca_topic_score_gemma":0.000636577,"domain_scores_codex":[0.9974862,0.0002653599,0.0009292227,0.0007431869,0.0001739144,0.0004021142],"domain_scores_gemma":[0.9986728,0.00007523494,0.0002829751,0.000584951,0.0002837949,0.0001002715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001242588,0.0003414739,0.9051548,0.0008485359,0.00008788963,0.00006378825,0.009755938,7.389564e-7,0.02279533,0.03092621,0.02212214,0.006660542],"study_design_scores_gemma":[0.006461645,0.005096613,0.8586249,0.001910827,0.00004635487,0.0002313147,0.004858023,0.00002422674,0.004548389,0.00523041,0.1126519,0.0003154523],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8769516,0.001819819,0.0000432744,0.009878263,0.008707652,0.001730864,0.000008015086,0.00003962402,0.1008209],"genre_scores_gemma":[0.9633291,0.002539512,0.0001435962,0.0002721437,0.03309354,0.00004719743,0.00003236128,0.00001857157,0.0005240147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1002969,"threshold_uncertainty_score":0.5824099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03821177319844556,"score_gpt":0.3469211390602871,"score_spread":0.3087093658618416,"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."}}