{"id":"W1686189390","doi":"10.1111/1745-5871.12102","title":"Mobile Adaptation and Sticky Experiments: Circulating Best Practices and Lessons Learned in Climate Change Adaptation","year":2015,"lang":"en","type":"article","venue":"Geographical Research","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Killam Trusts","keywords":"Adaptation (eye); Legitimacy; Mobilities; Psychological resilience; Work (physics); Political science; Climate change; Best practice; Geography; Sociology; Economic geography; Social science; Engineering; Social psychology; Ecology; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.08396275,0.0007776698,0.00104147,0.002183445,0.008203274,0.01293681,0.005298865,0.004515516,0.00878482],"category_scores_gemma":[0.08889514,0.0004515731,0.0006255109,0.002733325,0.03659865,0.01470996,0.01293863,0.006033331,0.0009230122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006444258,"about_ca_system_score_gemma":0.007856183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003300709,"about_ca_topic_score_gemma":0.005090326,"domain_scores_codex":[0.9324721,0.0599357,0.0008847637,0.002612512,0.002431408,0.001663626],"domain_scores_gemma":[0.8606613,0.115886,0.002508104,0.01494171,0.003527639,0.002475188],"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":[0.0004656576,0.0010853,0.005275955,0.001659092,0.0001402126,0.0007285274,0.2952894,0.00588533,0.002298699,0.3007499,0.009466012,0.376956],"study_design_scores_gemma":[0.0002298914,0.001149364,0.004177858,0.004233128,0.00009789538,0.0004331091,0.2443368,0.004805387,0.003412171,0.5217047,0.2152222,0.00019755],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4068782,0.0232707,0.1756551,0.192457,0.002293488,0.001123222,0.0001699069,0.0009485102,0.1972039],"genre_scores_gemma":[0.9559335,0.00408433,0.03288939,0.002612034,0.0001728862,0.0004754154,0.00003091521,0.0001433456,0.003658227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08396275,"threshold_uncertainty_score":0.4440428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7174564272508497,"score_gpt":0.5353642695831288,"score_spread":0.1820921576677209,"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."}}