{"id":"W2099021621","doi":"10.1186/2212-9790-11-3","title":"Adaptive learning, technological innovation and livelihood diversification: the adoption of pound nets in Rio de Janeiro State, Brazil","year":2012,"lang":"en","type":"article","venue":"MAST. Maritime studies/Maritime studies","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Social Sciences and Humanities Research Council of Canada; International Development Research Centre; University of Manitoba","keywords":"Diversification (marketing strategy); Livelihood; Restructuring; Fishing; Pound (networking); Narrative; Economy; Business; Environmental resource management; Knowledge management; Economics; Geography; Political science; Marketing; Computer science; Agriculture; Finance","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":[0.001631244,0.0001402954,0.00019936,0.00082996,0.001961757,0.001640153,0.0006168907,0.0005343568,0.0008184739],"category_scores_gemma":[0.004745294,0.0002060353,0.0001274303,0.0009337559,0.002963856,0.0009844843,0.002143507,0.0006140987,0.00004580394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003946231,"about_ca_system_score_gemma":0.00330909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07195155,"about_ca_topic_score_gemma":0.189783,"domain_scores_codex":[0.9990915,0.0004190851,0.0000382662,0.00009172533,0.0001610863,0.0001983428],"domain_scores_gemma":[0.9982051,0.0008864094,0.000479306,0.00007648161,0.0001400834,0.0002127038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004436924,0.0001371937,0.1703981,0.0002803225,0.0000190596,0.003275754,0.7674863,0.0002498534,0.004192739,0.01189298,0.0003563812,0.04166696],"study_design_scores_gemma":[0.000008460854,0.000168371,0.3355972,0.0002957052,0.00002116918,0.0009702401,0.6276697,0.0005739334,0.0007100537,0.001206489,0.03274614,0.0000325717],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956079,0.0002542046,0.00009531245,0.0006244919,0.000002900257,0.00001438243,0.000007213575,0.000001403415,0.003392106],"genre_scores_gemma":[0.9991623,0.0002855927,0.0001232112,0.00003814252,0.000001086987,0.000007521481,0.000004330177,8.214174e-7,0.0003770085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07195155,"threshold_uncertainty_score":0.1430655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04117963610466074,"score_gpt":0.2715281126078689,"score_spread":0.2303484765032082,"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."}}