{"id":"W4413075120","doi":"10.2139/ssrn.5355899","title":"Vulnerability Metrics and Climate Analogues Inform Tree Species Selection and Climate Bottleneck in a Changing Climate","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Université Laval; Université du Québec en Outaouais","funders":"","keywords":"Vulnerability (computing); Climate change; Bottleneck; Environmental resource management; Selection (genetic algorithm); Environmental science; Ecology; Geography; Computer science; Biology","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":[0.001632787,0.0002929209,0.000570135,0.001357177,0.0003397538,0.00174473,0.0003429132,0.0006563966,0.00484782],"category_scores_gemma":[0.01293187,0.0002495971,0.0002847614,0.001651599,0.0004621346,0.001964071,0.000837415,0.0005781295,0.0004135051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002954846,"about_ca_system_score_gemma":0.0002518578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00199819,"about_ca_topic_score_gemma":0.003034811,"domain_scores_codex":[0.9996492,0.0001484944,0.00001721209,0.0001138243,0.00003046496,0.00004089399],"domain_scores_gemma":[0.99371,0.004307894,0.0009272147,0.0003691393,0.0002495693,0.0004361419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007925271,0.00009313584,0.8578334,0.0001230741,0.0003890202,0.0003171834,0.0007272284,0.07938134,0.00590351,0.006687433,0.002369969,0.04538211],"study_design_scores_gemma":[0.00004126956,0.0001658239,0.6648871,0.00003336859,0.000146815,0.0003026185,0.000959462,0.2899767,0.001194773,0.04041645,0.001817246,0.00005840418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893129,0.0001368364,0.008287645,0.0001753397,0.00001432203,0.000004829466,0.0006144529,0.00007310906,0.00138058],"genre_scores_gemma":[0.9983875,0.00003668394,0.001073485,0.00001321428,0.00001207808,0.000002468429,0.0003008719,0.00002828294,0.0001454808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00484782,"threshold_uncertainty_score":0.01621759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885931488570885,"score_gpt":0.2632011375572165,"score_spread":0.2443418226715077,"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."}}