{"id":"W3107465245","doi":"10.1111/jbi.14019","title":"Improving biological relevance of model projections in response to climate change by considering dispersal amongst lineages in an amphibian","year":2020,"lang":"en","type":"article","venue":"Journal of Biogeography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Agence Nationale de la Recherche; Direction Régionale de l'Environnement, de l'Aménagement et du Logement PACA","keywords":"Biological dispersal; Ecological niche; Biology; Ecology; Environmental niche modelling; Lineage (genetic); Last Glacial Maximum; Climate change; Phylogeography; Extinction (optical mineralogy); Niche; Glacial period; Habitat; Phylogenetics; Population","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":[0.0009592829,0.0006279348,0.0003741172,0.0005784216,0.0004520883,0.00110231,0.0008542866,0.0009368258,0.00316428],"category_scores_gemma":[0.003354574,0.0004881053,0.0007914896,0.0004149743,0.0002640762,0.0007116653,0.0004939893,0.0007073949,0.0002897669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006658232,"about_ca_system_score_gemma":0.0006799871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02097212,"about_ca_topic_score_gemma":0.01567541,"domain_scores_codex":[0.9997212,0.0001567193,0.00001616103,0.00006434917,0.00001721355,0.00002428298],"domain_scores_gemma":[0.998997,0.0006367654,0.00009751183,0.00006968843,0.0001322545,0.00006670065],"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":[0.00003409597,0.0000163854,0.0110246,0.00002055415,0.00007800737,0.00003699211,0.0000269367,0.9861255,0.0003353843,0.00045564,0.0002092052,0.001636605],"study_design_scores_gemma":[0.00001780929,0.00002394791,0.004394446,0.00001663387,0.00004393698,0.0000245135,0.00005560748,0.9939063,0.0001798915,0.0007788161,0.0005445014,0.00001360315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618108,0.0002828505,0.03081179,0.0006095212,0.00006043187,0.00003150383,0.00163849,0.0003748303,0.004379785],"genre_scores_gemma":[0.9938276,0.00008394981,0.00486313,0.00004208812,0.00001300474,0.00002827819,0.0005980403,0.00005468968,0.0004891204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02097212,"threshold_uncertainty_score":0.04170007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05421492200856518,"score_gpt":0.2779712190142006,"score_spread":0.2237562970056354,"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."}}