{"id":"W2012646360","doi":"10.1007/s11692-008-9036-5","title":"Modifier Selection by Transgenes: The Case of Growth Hormone Transgenesis and Hyperactive Circling Mice","year":2008,"lang":"en","type":"article","venue":"Evolutionary Biology","topic":"Animal Genetics and Reproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Transgenesis; Selection (genetic algorithm); Transgene; Biology; Growth hormone; Genetics; Biotechnology; Hormone; Endocrinology; Gene; Computer science; Artificial intelligence; Embryogenesis; Reproductive technology","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":[0.0001070757,0.0001157441,0.0001201622,0.00003112682,0.0002547441,0.0000018422,0.00006533158,0.0001628308,0.000005485216],"category_scores_gemma":[0.00002324033,0.00009031747,0.00006150077,0.00009866227,0.0003171329,0.000004301302,0.00002043691,0.0000747179,0.000001115768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009161656,"about_ca_system_score_gemma":0.00004473628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002248022,"about_ca_topic_score_gemma":0.00001391473,"domain_scores_codex":[0.9991832,0.0001038752,0.0001790352,0.0003458874,0.00003739283,0.0001506531],"domain_scores_gemma":[0.9996379,0.00001980238,0.00006596519,0.0001157924,0.0001240836,0.00003646305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001500315,0.00006058668,0.002241013,0.000006143099,0.00006648478,0.000004138466,0.0001029462,0.00006403478,0.9957785,0.0001135061,0.0007153671,0.0006972729],"study_design_scores_gemma":[0.001708466,0.003003004,0.0762502,0.000007613959,0.0001755088,0.01456278,0.0008151314,0.001588086,0.8781913,0.0006941879,0.02229083,0.000712927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796513,0.01114026,0.008542337,0.0002952532,0.00008121571,0.0001457998,0.000048389,0.000007408034,0.00008806709],"genre_scores_gemma":[0.9951105,0.003925886,0.0004040949,0.00005294092,0.0001944202,0.00001793146,0.00007386362,0.00001204021,0.0002083028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1175872,"threshold_uncertainty_score":0.3683039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124421090419286,"score_gpt":0.2315324524711099,"score_spread":0.220288241566917,"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."}}