{"id":"W2531864606","doi":"10.1108/ijccsm-04-2015-0038","title":"Governance and climate variability in Chinchiná River, Colombia","year":2016,"lang":"en","type":"article","venue":"International Journal of Climate Change Strategies and Management","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Corporate governance; Vulnerability (computing); Climate change; Government (linguistics); Agriculture; Environmental resource management; Adaptive capacity; Psychological resilience; Originality; Environmental planning; Political science; Geography; Business; Qualitative research; Sociology; Economics; Ecology; Social 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004792373,0.0001214416,0.0001640729,0.00001841145,0.0000523977,0.0001644974,0.0002076429,0.00004003556,0.00005103314],"category_scores_gemma":[0.00001285976,0.00003949089,0.00003943095,0.00006470576,0.00005288203,0.0007651387,0.0002202462,0.00006065506,0.000002105439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006028245,"about_ca_system_score_gemma":0.00000319935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005837428,"about_ca_topic_score_gemma":0.0004337765,"domain_scores_codex":[0.9989978,0.00004806123,0.000318135,0.0001671317,0.0002676068,0.0002012571],"domain_scores_gemma":[0.9995109,0.00008372156,0.0002383097,0.00002457294,0.00008366285,0.0000588333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000317596,0.0001717938,0.07363117,0.00006399475,0.0001051176,0.0001679419,0.0004463082,0.000001123439,0.0006888127,0.2346643,0.0002343705,0.6895074],"study_design_scores_gemma":[0.0005292561,0.0001088168,0.9757152,0.0002291275,0.00001053239,0.00003271531,0.0006735119,0.000005507221,0.00003502501,0.01547407,0.00706741,0.0001188405],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944528,0.0002741556,0.00001026503,0.002634899,0.0003645688,0.0001607625,0.00005812863,0.000009252361,0.002035112],"genre_scores_gemma":[0.9487026,0.05074294,0.0001614689,0.0001586707,0.0001878488,0.00001005831,0.000005182324,7.970698e-7,0.00003049288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.902084,"threshold_uncertainty_score":0.1610392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0182830132778556,"score_gpt":0.2408266349385293,"score_spread":0.2225436216606738,"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."}}