{"id":"W4234498033","doi":"10.3410/f.1088785.541881","title":"Faculty Opinions recommendation of Gene flow in complex landscapes: testing multiple hypotheses with causal modeling.","year":2007,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Gene flow; Flow (mathematics); Computational biology; Computer science; Data science; Psychology; Gene; Biology; Genetics; Mathematics","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":[0.003478219,0.002913418,0.002248887,0.004524624,0.0009229467,0.00303829,0.00530732,0.003452003,0.04029763],"category_scores_gemma":[0.02153487,0.001060466,0.002299523,0.005586965,0.0005000369,0.001570569,0.001840368,0.002550944,0.03913686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00174864,"about_ca_system_score_gemma":0.003181119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02616877,"about_ca_topic_score_gemma":0.06101369,"domain_scores_codex":[0.9980599,0.000492704,0.0001555325,0.0006326695,0.0004800728,0.0001790973],"domain_scores_gemma":[0.9926663,0.003269017,0.0005572737,0.00190337,0.001003038,0.0006010696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009980407,0.00006176013,0.003747251,0.0004559082,0.0001536413,0.00002992652,0.00001876089,0.0009530153,0.0001150217,0.0004821602,0.9889415,0.004941289],"study_design_scores_gemma":[0.001970651,0.0000881446,0.02757191,0.0005156062,0.0004590957,0.0002646234,0.0001616426,0.02040295,0.002064,0.007607553,0.9387797,0.0001140456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001236756,0.0001445003,0.0006251697,0.0003661043,0.00006930481,0.00003360448,0.9949504,0.001352318,0.001221797],"genre_scores_gemma":[0.002073667,0.00006186656,0.00179941,0.0001054421,0.00001824476,0.0000778814,0.994431,0.0001428097,0.001289725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04029763,"threshold_uncertainty_score":0.134809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07144119800575309,"score_gpt":0.3582027726948567,"score_spread":0.2867615746891036,"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."}}