{"id":"W6910922361","doi":"10.5061/dryad.44hh4pj","title":"Data from: Female preference for novel males constrains contemporary evolution of assortative mating in guppies","year":2018,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Assortative mating; Sexual selection; Mate choice; Adaptation (eye); Population; Selection (genetic algorithm); Experimental evolution; Mating preferences; Preference; Local adaptation","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","open_science"],"consensus_categories":[],"category_scores_codex":[0.002343385,0.0008633207,0.001392866,0.0004196434,0.0003158445,0.0002106528,0.006409701,0.0003569523,0.00003420393],"category_scores_gemma":[0.0003364444,0.0008388499,0.00006429675,0.0003910873,0.0008414352,0.001581133,0.005135886,0.000719871,0.00003957348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009055208,"about_ca_system_score_gemma":0.0004589907,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02380608,"about_ca_topic_score_gemma":0.1584208,"domain_scores_codex":[0.9943389,0.0005350399,0.001508102,0.002231264,0.0005865339,0.0008001465],"domain_scores_gemma":[0.9899386,0.002878131,0.001984113,0.004864864,0.0001461399,0.0001881215],"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":[0.0009241831,0.0004778098,0.02168334,0.004295844,0.0008574097,0.00001521654,0.002923625,0.0001201563,0.001152212,0.00003391918,0.9671289,0.000387438],"study_design_scores_gemma":[0.005139494,0.0004437159,0.1003138,0.02451705,0.001172424,0.00002745942,0.01004992,0.4122349,0.00003718723,0.0009078057,0.4423136,0.00284271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04088642,0.001353558,0.001802037,0.00001043304,0.0002695325,0.001206299,0.9542551,0.00008474527,0.0001318701],"genre_scores_gemma":[0.05355882,0.0002315675,0.009828172,0.00003456179,0.0005028177,0.0000772151,0.935644,0.0001108262,0.00001205508],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5248153,"threshold_uncertainty_score":0.9994062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1778150067578023,"score_gpt":0.3367547425228904,"score_spread":0.1589397357650882,"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."}}