{"id":"W4303859828","doi":"10.1111/ddi.13630","title":"Migration‐based simulations for Canadian trees show limited tracking of suitable climate under climate change","year":2022,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vineland Research and Innovation Centre; Université de Sherbrooke; Natural Resources Canada; McGill University; Canadian Forest Service","funders":"","keywords":"Biological dispersal; Habitat; Range (aeronautics); Representative Concentration Pathways; Species distribution; Climate change; Ecology; Environmental science; Physical geography; Climatology; Climate model; Geography; Geology; Biology; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001677138,0.00009836732,0.000117203,0.00006567973,0.004377758,0.00002869314,0.0001393746,0.00004541244,0.0106088],"category_scores_gemma":[0.00003312327,0.0001154804,0.00007890315,0.0003725547,0.0001287683,0.000213686,0.000458623,0.00007556583,0.00001317038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005806496,"about_ca_system_score_gemma":0.00001661457,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02448851,"about_ca_topic_score_gemma":0.181323,"domain_scores_codex":[0.9990765,0.00003834568,0.0001334647,0.0002053372,0.000179307,0.000367047],"domain_scores_gemma":[0.9995186,0.00008231313,0.00007315155,0.0001331494,0.00003251666,0.0001602717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006385049,0.0003090966,0.9631987,0.0000269887,0.0000201044,0.000002468698,0.001025014,0.003874989,0.0005028334,0.02714913,0.003497345,0.0003294604],"study_design_scores_gemma":[0.000840669,0.0001009186,0.9611792,0.000005921552,0.00009293548,0.000001833453,0.005241694,0.01046208,0.0001977216,0.0002453076,0.02139874,0.000233008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9521317,0.00003530964,0.0006335921,0.001822785,0.00008581754,0.0003788319,0.0439842,0.00003643618,0.0008913309],"genre_scores_gemma":[0.9951084,0.00002987742,0.00003538751,0.0003080081,0.000009546403,0.00004294931,0.004435904,0.000004600106,0.00002535918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1568345,"threshold_uncertainty_score":0.9969184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07633178174462804,"score_gpt":0.2518016210895621,"score_spread":0.1754698393449341,"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."}}