{"id":"W4237878341","doi":"10.21275/v5i2.nov161298","title":"Supporting Aquaculture in Ghana with Hydrographic Data","year":2016,"lang":"en","type":"article","venue":"International Journal of Science and Research (IJSR)","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aquaculture; Hydrography; Fishery; Geography; Hydrographic survey; Oceanography; Environmental science; Fish <Actinopterygii>; Cartography; Geology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006663654,0.00006284416,0.00009206565,0.0004298044,0.0001542944,0.00018604,0.002128139,0.00002849042,0.001031916],"category_scores_gemma":[0.001021292,0.00003128987,0.00001515641,0.0009881799,0.002919433,0.001799659,0.001327149,0.0003180433,0.00001809436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001629107,"about_ca_system_score_gemma":0.0002013716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003264359,"about_ca_topic_score_gemma":0.000231573,"domain_scores_codex":[0.9956917,0.00006616683,0.0002549367,0.000274201,0.00328696,0.0004261026],"domain_scores_gemma":[0.9989901,0.0001332025,0.00009713521,0.0002134042,0.0003576408,0.000208545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001645768,0.0001086886,0.7150479,0.000003445794,0.00001750069,0.000459227,0.0004836132,0.000003344873,0.02002296,0.0002037401,0.002443658,0.2610413],"study_design_scores_gemma":[0.005081228,0.001822909,0.6215338,0.0005321451,0.00001147472,0.00203647,0.009013291,0.003706997,0.008110742,0.006304659,0.3411422,0.0007040901],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610209,0.00002313348,0.00009627383,0.01033487,0.00008236004,0.00008753498,0.000006626677,0.000003050235,0.02834521],"genre_scores_gemma":[0.9980896,0.0002161972,0.0005901516,0.00007406878,0.00007902057,0.000001620049,8.081929e-7,0.000004008416,0.000944591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3386986,"threshold_uncertainty_score":0.9998813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05499679196106088,"score_gpt":0.3943089936588401,"score_spread":0.3393122016977792,"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."}}