{"id":"W6999316083","doi":"","title":"Climate change and citizenship : a case study of responses in Canadian coastal communities","year":2006,"lang":"en","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Citizenship; Government (linguistics); Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.002089584,0.0004237838,0.0003751622,0.001747992,0.02785225,0.002717632,0.002157434,0.002205754,0.002771539],"category_scores_gemma":[0.004025318,0.0002822301,0.0003383287,0.004661665,0.005543097,0.00116353,0.004389985,0.00164098,0.000161133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03065551,"about_ca_system_score_gemma":0.03230606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9583799,"about_ca_topic_score_gemma":0.9905821,"domain_scores_codex":[0.9978497,0.0006900096,0.00003978319,0.0001187583,0.0002805756,0.001021168],"domain_scores_gemma":[0.9970175,0.0009277651,0.000298696,0.0001572168,0.0006346805,0.0009642066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001179275,0.0003110597,0.09500345,0.0001157974,0.00002840418,0.007208752,0.8652455,0.0003011585,0.0005595852,0.002838768,0.004126282,0.02414328],"study_design_scores_gemma":[0.00000811806,0.00004995431,0.05108582,0.00005455114,0.00001339235,0.0004024327,0.936497,0.0001352835,0.0001318322,0.0002006821,0.01140262,0.00001823947],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989355,0.0002658875,0.00008997034,0.001113792,0.00001396104,0.00006029359,0.00007665627,0.000004323731,0.009020209],"genre_scores_gemma":[0.9956076,0.0004059733,0.0002492103,0.0002028863,0.000005631325,0.00003214158,0.0000557356,0.00000467468,0.003436356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04162014,"threshold_uncertainty_score":0.2224223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1163091890660633,"score_gpt":0.3370146335730579,"score_spread":0.2207054445069945,"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."}}