{"id":"W1985370407","doi":"10.1007/s10113-012-0297-2","title":"Climate change adaptation planning in remote, resource-dependent communities: an Arctic example","year":2012,"lang":"en","type":"article","venue":"Regional Environmental Change","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Guelph","funders":"","keywords":"Environmental resource management; Adaptation (eye); Vulnerability (computing); Context (archaeology); Climate change; Environmental planning; Resource (disambiguation); Participatory planning; Geography; Subsistence agriculture; Political science; Business; Agriculture; Ecology; Economics; Computer science","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":[0.002276997,0.0002267658,0.0002696925,0.0006877161,0.0133868,0.002859647,0.0007994967,0.001187659,0.001940846],"category_scores_gemma":[0.00226048,0.0001100322,0.0004448114,0.001528206,0.002127758,0.0008725824,0.00237944,0.001369749,0.0001530741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003830587,"about_ca_system_score_gemma":0.01119155,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2869872,"about_ca_topic_score_gemma":0.6252096,"domain_scores_codex":[0.9987054,0.0007505642,0.00001810616,0.00003971885,0.000131617,0.0003545888],"domain_scores_gemma":[0.998333,0.0006550965,0.00008880457,0.00009590624,0.0003057373,0.000521409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009222512,0.003457205,0.1157912,0.0008464186,0.0002883863,0.02231104,0.2217761,0.0485487,0.004782991,0.2494664,0.02817045,0.3036389],"study_design_scores_gemma":[0.0001865222,0.0007174155,0.08067451,0.0007286916,0.0002428174,0.002667718,0.571123,0.01969343,0.002441273,0.06603344,0.2553554,0.0001357868],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7642838,0.001722741,0.008589173,0.01622522,0.0002840872,0.0001533217,0.0001021205,0.00005235081,0.2085871],"genre_scores_gemma":[0.9776658,0.00225069,0.008003202,0.0007274875,0.00009401257,0.00005963642,0.00004257059,0.00002010336,0.01113642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7130128,"threshold_uncertainty_score":0.5706335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2910067223031281,"score_gpt":0.3717264588795763,"score_spread":0.08071973657644821,"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."}}