{"id":"W2283106792","doi":"10.5539/jas.v8n6p169","title":"Awareness, Training Needs and Constraints on Fishing Technologies among Small Scale Fishermen in Ondo State, Nigeria","year":2016,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Fisheries and Aquaculture Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fishing; Scale (ratio); Business; Training (meteorology); Local government area; Government (linguistics); Fish processing; Fish <Actinopterygii>; Sample (material); Operations management; Environmental resource management; Fishery; Local government; Geography; Engineering; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005714903,0.0001871613,0.0003140967,0.00005359725,0.0003505638,0.000214367,0.0004947541,0.00007489626,0.00003318777],"category_scores_gemma":[0.0003017074,0.00004698211,0.00007175129,0.0009227433,0.001236138,0.0008450089,0.0001435243,0.0001957455,0.0000015136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007976444,"about_ca_system_score_gemma":0.0000246935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006206605,"about_ca_topic_score_gemma":0.001789169,"domain_scores_codex":[0.9985042,0.00003679226,0.0003907307,0.0002469403,0.0003712592,0.0004500862],"domain_scores_gemma":[0.9991676,0.0001947365,0.0002967536,0.000038995,0.0001913121,0.0001105934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002623272,0.0000431421,0.29526,0.000004597673,0.0000100155,0.00001647155,0.001651088,0.000005124233,0.5194854,0.00003346075,0.0006308631,0.1828336],"study_design_scores_gemma":[0.0002250057,0.0003618154,0.9729237,0.0002542054,0.000003070943,0.00006055219,0.0191411,6.209285e-7,0.005981743,0.0002582573,0.0006085947,0.0001813192],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917876,0.00007899737,0.000001140274,0.006782244,0.0001684403,0.000105426,0.0000115036,0.00003657233,0.001028143],"genre_scores_gemma":[0.9993886,0.0002003347,0.0001291407,0.00006555487,0.00008810294,0.0000032913,5.860276e-7,6.985442e-7,0.0001236778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6776637,"threshold_uncertainty_score":0.4554601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01913975399039,"score_gpt":0.2086133763062946,"score_spread":0.1894736223159046,"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."}}