{"id":"W6929606046","doi":"10.5061/dryad.782s82b","title":"Data from: Turning down the heat: vegetation feedbacks limit fire regime responses to global warming","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Climate change; Vegetation (pathology); Global warming; Taiga; Abies balsamea; Global change; Disturbance (geology); Boreal","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004435128,0.0004063693,0.0002672664,0.0002310961,0.0004700435,0.0008497228,0.0007907814,0.0007148052,0.007884315],"category_scores_gemma":[0.00190323,0.0001895109,0.0004653661,0.0006138082,0.000229658,0.0003832277,0.0002272532,0.0005002648,0.001501831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00284034,"about_ca_system_score_gemma":0.002673673,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7810173,"about_ca_topic_score_gemma":0.803187,"domain_scores_codex":[0.9998457,0.00002817205,0.000009872724,0.00004471219,0.00003991877,0.00003155297],"domain_scores_gemma":[0.9990034,0.0001961718,0.00006415975,0.00008088963,0.0005565603,0.00009889542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008515369,0.0002570367,0.2653235,0.0006182165,0.000255178,0.0002022166,0.0003534191,0.5496055,0.003224564,0.001649471,0.1454321,0.03222722],"study_design_scores_gemma":[0.0007371428,0.0001324836,0.3269032,0.0002259335,0.0001771966,0.00005504534,0.0003699231,0.5590275,0.004709405,0.001310604,0.1062038,0.0001477561],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6792527,0.0004856036,0.005739453,0.002341375,0.0002554756,0.0002806113,0.281968,0.002118157,0.02755856],"genre_scores_gemma":[0.9036117,0.0002081039,0.004112179,0.0002970668,0.00004040584,0.0001326151,0.08561177,0.000159389,0.005826701],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.7810173,"threshold_uncertainty_score":0.4405446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03758995097501164,"score_gpt":0.3193073487013953,"score_spread":0.2817173977263837,"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."}}