{"id":"W2308768928","doi":"10.1007/s11367-016-1092-y","title":"Review and advancement of the marine biotic resource use metric in seafood LCAs: a case study of Norwegian salmon feed","year":2016,"lang":"en","type":"article","venue":"The International Journal of Life Cycle Assessment","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Environmental science; Ecosystem; Resource (disambiguation); Metric (unit); Ecosystem-based management; Production (economics); Aquaculture; Marine ecosystem; Environmental resource management; Fishery; Computer science; Ecology; Fish <Actinopterygii>; Biology; Engineering; Operations management","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":[0.00609083,0.000564991,0.001308578,0.00471443,0.0003265211,0.002430011,0.001029191,0.0008608511,0.001667182],"category_scores_gemma":[0.01166725,0.0003838379,0.001162843,0.009320521,0.0008903349,0.001554277,0.000593789,0.0008987011,0.0002747686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002666701,"about_ca_system_score_gemma":0.006825897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02256304,"about_ca_topic_score_gemma":0.03535877,"domain_scores_codex":[0.9980146,0.0005663342,0.0005079028,0.0003101327,0.0005394903,0.00006147591],"domain_scores_gemma":[0.9854125,0.01033196,0.00140123,0.0002801632,0.002406961,0.0001671457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002069577,0.00007375408,0.009752489,0.05532707,0.0008471069,0.0003249534,0.0007589917,0.00153288,0.001334492,0.006313062,0.01659879,0.9069296],"study_design_scores_gemma":[0.00003000933,0.000328174,0.05148892,0.07440446,0.003293901,0.00113025,0.002352825,0.001515158,0.001580276,0.003708975,0.8600408,0.0001262692],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004337461,0.9904382,0.0007199109,0.001288762,0.0003725024,0.00001655076,0.000241901,0.000007692363,0.002577199],"genre_scores_gemma":[0.03470431,0.9607886,0.00265984,0.0007136315,0.0002808996,0.00002138551,0.000260804,0.00001304504,0.0005573404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02256304,"threshold_uncertainty_score":0.0448634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02624847191462681,"score_gpt":0.3196962408990761,"score_spread":0.2934477689844492,"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."}}