{"id":"W4414770190","doi":"10.1101/2025.09.30.679621","title":"Population-level migration modeling of North America’s birds through data integration with BirdFlow","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Birds Canada","funders":"U.S. Geological Survey; Massachusetts Green High Performance Computing Center; National Science Foundation","keywords":"Global Positioning System; Data integration; Data modeling; Probabilistic logic; Generalizability theory; Tracking (education); Movement (music); Statistical model","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":[0.002373284,0.00058206,0.0004019498,0.0009187186,0.000411449,0.0007035341,0.001199487,0.0006277544,0.0008769935],"category_scores_gemma":[0.007378821,0.0003977328,0.0008685125,0.0005552269,0.000455017,0.000881993,0.0007828063,0.000929858,0.0001669551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000995247,"about_ca_system_score_gemma":0.0007624276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06170944,"about_ca_topic_score_gemma":0.04688959,"domain_scores_codex":[0.9996431,0.0001378664,0.00002185599,0.0001245811,0.00003908659,0.00003351227],"domain_scores_gemma":[0.9979849,0.001182923,0.0002454528,0.0002395418,0.0002450568,0.000102141],"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":[0.00004060111,0.00006273352,0.03155051,0.00001789362,0.00009661452,0.00003404243,0.00006765151,0.9567929,0.000413434,0.0005296355,0.0004655268,0.009928502],"study_design_scores_gemma":[0.00000360905,0.000006180699,0.00303491,0.000003737927,0.000004712919,0.000006073687,0.0000083309,0.9962975,0.00009064039,0.0004046141,0.0001353201,0.000004320522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8738376,0.0002201517,0.1204094,0.0004715573,0.00005359787,0.00006390522,0.001389284,0.002489112,0.001065327],"genre_scores_gemma":[0.9669861,0.00004583917,0.03102802,0.00005381907,0.00001917683,0.00004329407,0.001448127,0.00009023672,0.0002853906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06170944,"threshold_uncertainty_score":0.1227005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05361210104635322,"score_gpt":0.2534756897981578,"score_spread":0.1998635887518045,"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."}}