{"id":"W6892106963","doi":"10.5061/dryad.dfn2z356x","title":"Data from: Strong selection is poorly aligned with genetic variation in Ipomoea hederacea","year":2023,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Genetic variation; Trait; Population; Genetic divergence; Quantitative genetics; Natural selection; Covariance; Divergence (linguistics)","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":[0.001711033,0.001150258,0.001304889,0.0020496,0.00104113,0.001456902,0.001847193,0.00145789,0.01415696],"category_scores_gemma":[0.004070097,0.000361625,0.001124133,0.003333888,0.0005779226,0.0007377094,0.001584267,0.001010542,0.014255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008307801,"about_ca_system_score_gemma":0.001228295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01744429,"about_ca_topic_score_gemma":0.03644547,"domain_scores_codex":[0.999047,0.0002424608,0.00009338615,0.0003525891,0.0001491306,0.0001154432],"domain_scores_gemma":[0.9982144,0.0007413501,0.0002436628,0.0003703221,0.0002908482,0.0001394127],"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":[0.0009101724,0.0001564816,0.02943454,0.004327243,0.0005708617,0.0003091492,0.0003699445,0.00295249,0.003412074,0.001262401,0.9391384,0.01715628],"study_design_scores_gemma":[0.001188778,0.00009117624,0.1074306,0.0005540233,0.0003073704,0.0003531549,0.0004548312,0.002600981,0.001932241,0.001930754,0.8830417,0.0001143489],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008423796,0.0004997264,0.0002528202,0.0001967948,0.00004140359,0.00001529631,0.9891052,0.0004766617,0.0009882837],"genre_scores_gemma":[0.007003037,0.0001225211,0.0006291644,0.00009113509,0.000008290939,0.00007062402,0.9914525,0.00007121725,0.0005516114],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01744429,"threshold_uncertainty_score":0.04735976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08153991342583754,"score_gpt":0.348733724099158,"score_spread":0.2671938106733204,"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."}}