{"id":"W4416951872","doi":"10.21203/rs.3.rs-8108392/v1","title":"Predicting Migratory Survival in a Songbird Hybrid Zone Using Machine Learning","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Songbird; Hybrid; Hybrid zone; Random forest; Selection (genetic algorithm); Proxy (statistics)","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":[0.0004269266,0.0002368804,0.0002784071,0.0005376965,0.0002261636,0.0004486865,0.0003872636,0.0004283462,0.0007581164],"category_scores_gemma":[0.001172795,0.0001481741,0.0002470995,0.0003070046,0.0002146127,0.0003229438,0.0002042596,0.0003069162,0.0001753201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003692021,"about_ca_system_score_gemma":0.0001559071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005903436,"about_ca_topic_score_gemma":0.007280667,"domain_scores_codex":[0.9999385,0.00001552444,0.00000287951,0.0000253897,0.0000057098,0.00001202303],"domain_scores_gemma":[0.9993262,0.0004532901,0.00007513842,0.00003320197,0.00005609134,0.00005602526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004282884,0.0001786719,0.2897098,0.00004692857,0.0001590343,0.0001269493,0.00007982513,0.6413997,0.007847751,0.000805261,0.0008600487,0.0583577],"study_design_scores_gemma":[0.0000061351,0.00002723272,0.02982341,0.000002497679,0.00001126306,0.0000195807,0.000023556,0.9684404,0.000622167,0.0009684323,0.0000506029,0.000004793447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835082,0.00008961913,0.01575609,0.00008537534,0.000008023741,0.000003913369,0.0001700068,0.00006474629,0.0003140524],"genre_scores_gemma":[0.9964287,0.00001735539,0.003059395,0.000007048974,0.00000760957,0.000002996177,0.0001664662,0.000004521637,0.0003059365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005903436,"threshold_uncertainty_score":0.01173812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05225497352242613,"score_gpt":0.3585767259200132,"score_spread":0.306321752397587,"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."}}