{"id":"W1575322853","doi":"10.3390/su7079268","title":"Prioritizing Climate Change Adaptations in Canadian Arctic Communities","year":2015,"lang":"en","type":"article","venue":"Sustainability","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; International Development Research Centre; Canadian Institutes of Health Research; ArcticNet","keywords":"Adaptation (eye); Climate change; Prioritization; Environmental resource management; Arctic; Vulnerability (computing); Sustainability; Climate change adaptation; Environmental planning; Equity (law); The arctic; Computer science; Process (computing); Environmental science; Business; Process management; Ecology; Political science","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.002389658,0.00009908093,0.0002128492,0.0001621691,0.002758829,0.000006131192,0.0001277168,0.0001330387,0.00006115197],"category_scores_gemma":[0.001530482,0.0001004476,0.00002646576,0.000221646,0.0001018952,0.0001165069,0.0001845737,0.0005018926,0.00006141153],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01277133,"about_ca_system_score_gemma":0.005127911,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9829906,"about_ca_topic_score_gemma":0.9991956,"domain_scores_codex":[0.9971167,0.0006542948,0.0003129333,0.0001237877,0.00007845514,0.001713792],"domain_scores_gemma":[0.9974213,0.000298645,0.00005981232,0.0003023405,0.001651493,0.0002663668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001305545,0.00002528471,0.709808,0.0002255188,0.000003009109,0.00001289117,0.2731619,0.000004008912,2.341989e-8,0.01618969,0.00009794667,0.000458739],"study_design_scores_gemma":[0.0002570238,0.00004937915,0.4748566,0.00001934004,0.000003841024,6.098329e-7,0.5007094,0.0000769149,1.228681e-8,0.008130307,0.01582331,0.00007319434],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706447,0.0002885859,0.000002230182,0.01285055,0.000499086,0.001872673,0.00003099637,0.00004898369,0.01376218],"genre_scores_gemma":[0.997824,0.00006157949,0.00005573684,0.001047434,0.0001230881,0.0007272678,0.00001924784,0.0000123961,0.000129302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2349513,"threshold_uncertainty_score":0.9985394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1249051184240406,"score_gpt":0.414242038771715,"score_spread":0.2893369203476744,"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."}}