{"id":"W2981869548","doi":"10.1007/s10584-019-02571-x","title":"Adaptation to climate change in coastal communities: findings from seven sites on four continents","year":2019,"lang":"en","type":"article","venue":"Climatic Change","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Moncton","funders":"Social Sciences and Humanities Research Council of Canada; Ministry of Earth Sciences; Russian Foundation for Basic Research; Agence Nationale de la Recherche","keywords":"Climate change; Livelihood; Adaptation (eye); Environmental resource management; Geography; Temperate climate; Environmental change; Arctic; Ecology; Environmental science; Agriculture","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009721086,0.0002520623,0.0003827061,0.0003694054,0.0003248265,0.0001657292,0.0003507723,0.0001665817,0.001268503],"category_scores_gemma":[0.0002052733,0.0002774327,0.00008024933,0.0005753762,0.00007425276,0.0007364083,0.000124265,0.0001928151,0.001435758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003487055,"about_ca_system_score_gemma":0.00003419068,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0430713,"about_ca_topic_score_gemma":0.361978,"domain_scores_codex":[0.9976186,0.0003478192,0.0004568671,0.000319389,0.0006226643,0.0006346646],"domain_scores_gemma":[0.9984125,0.0007220294,0.0002075692,0.0003604529,0.000139026,0.0001584501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001055215,0.0001742713,0.170184,0.0001057814,0.00001413254,0.000005525832,0.8216784,0.00002126098,0.0002925215,0.001812598,0.0002722964,0.005333718],"study_design_scores_gemma":[0.002676862,0.0005246759,0.4832374,0.001890416,0.00005622831,0.000001160542,0.4822024,0.02159046,0.00007614098,0.001222665,0.005516515,0.001004992],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904056,0.00005669074,0.00003213215,0.003586052,0.0005817523,0.002230776,0.0003854664,0.000129886,0.002591596],"genre_scores_gemma":[0.9950311,0.0004179563,0.0004087359,0.002207557,0.0004145756,0.0005378765,0.0007302284,0.00004362078,0.0002083286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3394759,"threshold_uncertainty_score":0.9999678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2498028880422608,"score_gpt":0.3466853201314071,"score_spread":0.09688243208914629,"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."}}