{"id":"W7038232036","doi":"","title":"Impacts potentiels dâun changement climatique sur le pergélisol dans le nord canadien","year":2011,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Western europe; Statistical analysis; Limiting","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004393667,0.0006173039,0.0005579168,0.001024675,0.002070687,0.002280651,0.0006741902,0.0008605111,0.01468112],"category_scores_gemma":[0.0006081959,0.0002621078,0.000620477,0.001731584,0.0009694476,0.0007939201,0.001558677,0.0008451557,0.001127837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008985552,"about_ca_system_score_gemma":0.007148374,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5111958,"about_ca_topic_score_gemma":0.7021946,"domain_scores_codex":[0.9995751,0.00006783662,0.00001186107,0.00009424363,0.000151472,0.00009942043],"domain_scores_gemma":[0.999569,0.00006605411,0.00005050268,0.00002096333,0.00023889,0.0000545733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004715688,0.0005908336,0.2178217,0.006348763,0.001427391,0.005852596,0.0185862,0.09373851,0.1590229,0.04902103,0.03021535,0.4126591],"study_design_scores_gemma":[0.0001587301,0.001282011,0.3635378,0.001537659,0.001068329,0.0005562375,0.03568305,0.008188062,0.03676088,0.01202809,0.5388179,0.000381195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7882997,0.01589962,0.003520275,0.003950014,0.000629615,0.000141651,0.003728361,0.0002537053,0.183577],"genre_scores_gemma":[0.9045993,0.01198142,0.002335993,0.0006531478,0.00003267566,0.0001165562,0.001049309,0.0001103895,0.07912125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4888042,"threshold_uncertainty_score":0.9833657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00859964068162219,"score_gpt":0.1446835157665394,"score_spread":0.1360838750849172,"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."}}