{"id":"W6967131792","doi":"10.5061/dryad.ghx3ffbkc","title":"Data from: Artificial selection on sexual aggression: correlated traits and possible trade‐offs","year":2020,"lang":"en","type":"dataset","venue":"DRYAD","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Mating; Aggression; Sexual selection; Longevity; Selection (genetic algorithm); Mating preferences; Lineage (genetic); Mating system","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002976145,0.0007522079,0.0007992285,0.0003270601,0.0003159641,0.000296855,0.001077739,0.001021555,0.001047414],"category_scores_gemma":[0.0004378957,0.0007421821,0.00005400386,0.0008906052,0.0001517026,0.0003479685,0.0004208973,0.001917877,0.01894416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001366526,"about_ca_system_score_gemma":0.000366335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006103266,"about_ca_topic_score_gemma":0.002020983,"domain_scores_codex":[0.9956182,0.0003798594,0.0006788857,0.001892245,0.0008687433,0.0005620764],"domain_scores_gemma":[0.9977588,0.0002432263,0.0005870679,0.0009662049,0.00003706028,0.0004076455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007496829,0.0002924253,0.00001128433,0.00006163194,0.0002075718,0.0001942304,0.00009479762,0.00001038525,0.002521741,0.000002230779,0.9904576,0.005396421],"study_design_scores_gemma":[0.0008380011,0.0004451183,0.0007184765,0.0004943464,0.0005248642,0.00003053857,0.00005690186,0.002569393,0.0002620113,0.00004183755,0.9932,0.0008184981],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003558181,0.000521132,0.000004085213,0.0001979293,0.0009490695,0.0005575919,0.9938208,0.0003517516,0.00003945072],"genre_scores_gemma":[0.0004295807,0.000110678,0.00005957427,0.0003168373,0.00184424,0.00002156034,0.9969704,0.000172362,0.00007474398],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01789675,"threshold_uncertainty_score":0.9998658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08273428112302855,"score_gpt":0.3155970792256895,"score_spread":0.232862798102661,"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."}}