{"id":"W2197641783","doi":"","title":"VARIABILITY OF FISH PRODUCTION: NUTRIENTS AS CHEMICAL DRIVERS ACROSS A DIVERSE GEOGRAPHIC RANGE","year":2013,"lang":"en","type":"dissertation","venue":"Open ULeth Scholarship (OPUS) (University of Lethbridge)","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Lethbridge","keywords":"Nutrient; Fish <Actinopterygii>; Range (aeronautics); Production (economics); Fishery; Environmental science; Geography; Ecology; Biology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003109646,0.00009194241,0.0001674573,0.0003230039,0.0002318608,0.0005126113,0.0002108509,0.0002009672,0.001372827],"category_scores_gemma":[0.0007376208,0.000121629,0.0002455005,0.0009105813,0.0002967952,0.0003551353,0.0005491922,0.0002155713,0.0001766419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002939269,"about_ca_system_score_gemma":0.0002493875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02215645,"about_ca_topic_score_gemma":0.0403255,"domain_scores_codex":[0.9998368,0.00004022536,0.000007261133,0.00006465953,0.00002767487,0.00002340416],"domain_scores_gemma":[0.9996396,0.0001123917,0.000107986,0.00003328252,0.00005899437,0.00004767732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001564412,0.00002858771,0.9868299,0.00001291242,0.0001404876,0.00006135435,0.0005698805,0.0003585612,0.006298997,0.0001400443,0.0001566517,0.005246182],"study_design_scores_gemma":[7.039636e-7,0.000008568478,0.9994214,0.0000013624,0.00000773145,0.00001290488,0.0001927655,0.0001466129,0.00009076051,0.00002941629,0.00008630697,0.000001536707],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990665,0.00004860347,0.0001329831,0.00002993771,8.388761e-7,0.000001536854,0.0002335086,0.000002244174,0.0004839308],"genre_scores_gemma":[0.9993636,0.00003869238,0.0001055093,0.000009979648,0.000001464778,0.000002309911,0.0001945333,0.000002772855,0.000281179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02215645,"threshold_uncertainty_score":0.04405499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02411570258475586,"score_gpt":0.2549551659353282,"score_spread":0.2308394633505724,"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."}}