{"id":"W2160381002","doi":"10.1111/j.1365-2486.2011.02515.x","title":"Predicting phenology by integrating ecology, evolution and climate science","year":2011,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":430,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Center For Environmental Assessment; National Science Foundation","keywords":"Phenology; Ecology; Climate change; Temperate climate; Ecosystem; Niche; Habitat; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008687472,0.0003671059,0.0002410162,0.001178031,0.0002688589,0.000799901,0.0002748228,0.0004371308,0.0009663246],"category_scores_gemma":[0.002489613,0.0002258414,0.0003749137,0.0008815511,0.000341802,0.0009728943,0.0005201626,0.0003848178,0.0002081405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004488491,"about_ca_system_score_gemma":0.000563169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01105389,"about_ca_topic_score_gemma":0.01455738,"domain_scores_codex":[0.99983,0.00008823273,0.000007198026,0.00004298521,0.00001854363,0.00001303932],"domain_scores_gemma":[0.9991665,0.0004770721,0.0001538448,0.00005016808,0.00006024304,0.00009214543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008895267,0.00009599996,0.5631424,0.00009627106,0.0002356423,0.0000613236,0.0001304337,0.3632762,0.006361922,0.003054469,0.0006958244,0.06276052],"study_design_scores_gemma":[0.000009906244,0.0000548155,0.2135621,0.00001579069,0.00005504936,0.00006989606,0.00009304827,0.7758825,0.0007576142,0.00804408,0.001433524,0.00002161675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9053122,0.0009189388,0.08792801,0.0007815111,0.00001874778,0.00003262697,0.0008248559,0.0003215707,0.003861383],"genre_scores_gemma":[0.9853374,0.0002510409,0.01386863,0.00003825075,0.00001875455,0.00001043502,0.0002475456,0.00001432836,0.0002135703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01105389,"threshold_uncertainty_score":0.02197909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04354321414000598,"score_gpt":0.2690578746098258,"score_spread":0.2255146604698198,"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."}}