{"id":"W2285920049","doi":"","title":"Embryos without boundaries : breeding & selection","year":2011,"lang":"en","type":"article","venue":"Stockfarm","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Embryo; Selection (genetic algorithm); Sanctions; Biology; Biotechnology; Political science; Fishery; Law; Computer science; 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":[0.002925921,0.0002441013,0.0004630408,0.000932948,0.001768262,0.001860865,0.0006737554,0.0006229298,0.006480215],"category_scores_gemma":[0.002968414,0.000304728,0.0001409135,0.00117526,0.002304469,0.001179034,0.001688652,0.001446178,0.00165801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008172495,"about_ca_system_score_gemma":0.0008969897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001334205,"about_ca_topic_score_gemma":0.003894428,"domain_scores_codex":[0.9989854,0.0003844614,0.00005312481,0.0001465822,0.0003509238,0.000079492],"domain_scores_gemma":[0.9987185,0.0006334739,0.0001302748,0.000153533,0.0002067927,0.0001575009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001820155,0.00009827639,0.01225738,0.0001984692,0.00002460434,0.0009900643,0.002018723,0.001213523,0.03291379,0.2302845,0.01650358,0.7033151],"study_design_scores_gemma":[0.00007343922,0.000447886,0.04396149,0.0008261345,0.00007778973,0.004599585,0.002394113,0.002807351,0.02978919,0.2022276,0.7126397,0.0001556955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2500219,0.07615312,0.1889323,0.02148574,0.001685709,0.0004241531,0.000570279,0.0004788312,0.4602481],"genre_scores_gemma":[0.6443133,0.03583427,0.18607,0.004622205,0.000660689,0.0002992569,0.0006009351,0.0004731946,0.1271262],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.006480215,"threshold_uncertainty_score":0.02167851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06193505456082803,"score_gpt":0.3084497321645973,"score_spread":0.2465146776037692,"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."}}