{"id":"W6969403811","doi":"10.5683/sp3/xlbjqx","title":"Data for: Phenotypic extremes or extreme phenotypes? On the use of large and small-bodied 'phenocopied' Drosophila melanogaster males in studies of sexual selection and conflict","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Guelph; Wilfrid Laurier University","funders":"","keywords":"Mating; Sexual conflict; Sexual selection; Fecundity; Drosophila melanogaster; Selection (genetic algorithm); Reproductive success; Variation (astronomy); Drosophila (subgenus)","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":[0.008929482,0.0005964825,0.0009071243,0.002810808,0.001320841,0.001609302,0.001397774,0.002547938,0.04909931],"category_scores_gemma":[0.03816042,0.0003480127,0.0005749985,0.003916643,0.001930642,0.001774153,0.003082514,0.001928679,0.02069224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003668283,"about_ca_system_score_gemma":0.000574933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006768129,"about_ca_topic_score_gemma":0.001934599,"domain_scores_codex":[0.9877323,0.004743165,0.001901556,0.002161744,0.002789672,0.0006714621],"domain_scores_gemma":[0.9377661,0.03193704,0.007825725,0.01597765,0.004354633,0.002138824],"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":[0.005759038,0.001089884,0.1701857,0.007593374,0.0007011262,0.001882049,0.005006666,0.0007577744,0.04639748,0.02836074,0.5254899,0.2067763],"study_design_scores_gemma":[0.0003446984,0.0008953809,0.371766,0.002513593,0.0001924519,0.00217758,0.002431571,0.001159536,0.009940023,0.01004186,0.5982674,0.0002699126],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2119269,0.003468148,0.0305438,0.01544781,0.004441604,0.001371303,0.6359461,0.004795575,0.09205875],"genre_scores_gemma":[0.6454861,0.002632028,0.07521216,0.02107027,0.0008600531,0.008130342,0.2178025,0.003251631,0.02555495],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04909931,"threshold_uncertainty_score":0.1642535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5697213607419943,"score_gpt":0.4245306542113312,"score_spread":0.1451907065306631,"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."}}