{"id":"W2808046150","doi":"10.17501/iccc.2017.1201","title":"SHRIMP FARMERS’ COMPETENCE AND TRAINING NEEDS ON CLIMATE CHANGE ADAPTATION: A CASE STUDY FROM SOUTHWEST COASTAL BANGLADESH","year":2018,"lang":"en","type":"article","venue":"International conference on climate change","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre; Department for International Development; Government of the United Kingdom","keywords":"Shrimp; Competence (human resources); Adaptation (eye); Training (meteorology); Climate change; Fishery; Environmental resource management; Geography; Oceanography; Environmental science; Psychology; Meteorology; Geology; Biology; Management; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002607063,0.0002522564,0.0002075909,0.00005976763,0.0004538411,0.0003489032,0.0002592251,0.00008786295,0.00167227],"category_scores_gemma":[0.00003425259,0.0001149916,0.00004602022,0.0003222019,0.0001207342,0.0005794005,0.0001471463,0.0002048642,0.0001552929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002676513,"about_ca_system_score_gemma":0.000005592248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003739308,"about_ca_topic_score_gemma":0.0119609,"domain_scores_codex":[0.9984857,0.00009717798,0.000300069,0.0004234815,0.0003620417,0.0003315622],"domain_scores_gemma":[0.9989232,0.0002786366,0.0002605075,0.00007160435,0.0003598703,0.0001061693],"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":[0.001049999,0.001598754,0.1122548,0.00002437078,0.0002383039,0.001246394,0.1032313,0.000001060085,0.01874971,0.08486021,0.0001526185,0.6765924],"study_design_scores_gemma":[0.001194831,0.004767615,0.4772189,0.0004256798,0.0000703011,0.0003956276,0.5062787,0.002585167,0.0001777509,0.0005867786,0.005346118,0.0009525165],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869171,0.0000184063,0.000001280561,0.004048555,0.000535565,0.0004575125,0.001265995,0.0000801326,0.006675411],"genre_scores_gemma":[0.9965305,0.0001613881,0.00007620017,0.001202232,0.001476926,0.0001289629,0.000391541,0.000002807746,0.00002945021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6756399,"threshold_uncertainty_score":0.9992403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3318528867600725,"score_gpt":0.3433245187668195,"score_spread":0.01147163200674706,"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."}}