{"id":"W2754710967","doi":"10.3389/fmars.2017.00289","title":"Lessons from the First Generation of Marine Ecological Forecast Products","year":2017,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Horizon 2020; Maine Space Grant Consortium; Bundesministerium für Bildung und Forschung; Seventh Framework Programme; Innovationsfonden; European Commission; Norges Forskningsråd; National Aeronautics and Space Administration","keywords":"Livelihood; Marine fisheries; Environmental resource management; Computer science; Environmental science; Geography; Fishery; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02708906,0.001329173,0.001162427,0.002917661,0.0009189511,0.01130838,0.00378916,0.003862496,0.005392347],"category_scores_gemma":[0.07092379,0.0007259439,0.0009310672,0.002115682,0.002999589,0.02126951,0.004055426,0.009561331,0.004616743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002710241,"about_ca_system_score_gemma":0.003711821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009191852,"about_ca_topic_score_gemma":0.004245688,"domain_scores_codex":[0.9956084,0.001224761,0.0005783204,0.0005033388,0.001952761,0.0001324106],"domain_scores_gemma":[0.9574552,0.02305183,0.001478167,0.004049989,0.01210898,0.001855752],"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":[0.0002219961,0.0001040433,0.00597561,0.001350892,0.00009172248,0.0002917206,0.001391563,0.01440918,0.000864771,0.2810695,0.1632443,0.5309848],"study_design_scores_gemma":[0.00003535196,0.0001782235,0.002258527,0.003132243,0.00005539935,0.0002594134,0.0009756252,0.02240513,0.00132681,0.3197275,0.6494828,0.0001629548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.01964741,0.1477752,0.2417447,0.4948545,0.01528696,0.0002154991,0.007793934,0.003058746,0.06962292],"genre_scores_gemma":[0.246052,0.2084939,0.4628998,0.03273253,0.01657698,0.0004031937,0.01120441,0.002254305,0.01938285],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02708906,"threshold_uncertainty_score":0.1432623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04190229288124737,"score_gpt":0.2719855358340473,"score_spread":0.2300832429528,"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."}}