{"id":"W2981410078","doi":"10.1002/aqc.3133","title":"From one to ten: Canada's approach to achieving marine conservation targets","year":2019,"lang":"en","type":"article","venue":"Aquatic Conservation Marine and Freshwater Ecosystems","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Marine protected area; Marine conservation; Convention on Biological Diversity; Interim; Government (linguistics); Biodiversity; Environmental planning; Business; Environmental resource management; Enforcement; Conservation Plan; Ecosystem services; Fishery; Environmental protection; Geography; Ecosystem; Political science; Ecology; Environmental science; Habitat","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01939957,0.001368835,0.001122292,0.006299482,0.03980714,0.02784113,0.009611858,0.01568031,0.01404707],"category_scores_gemma":[0.03278551,0.0009657826,0.001537238,0.00552996,0.0139164,0.008771888,0.01705256,0.0230144,0.001603649],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1647127,"about_ca_system_score_gemma":0.6231931,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9794807,"about_ca_topic_score_gemma":0.9893252,"domain_scores_codex":[0.9587629,0.005442323,0.001347459,0.002781195,0.01797674,0.01368941],"domain_scores_gemma":[0.9321239,0.005057093,0.0009468264,0.0009942842,0.0285382,0.03233972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005141401,0.0001210436,0.005971717,0.0004291574,0.00005898234,0.001008858,0.01148945,0.001565672,0.0005681418,0.3820762,0.5205809,0.07607833],"study_design_scores_gemma":[0.00002720987,0.00009336474,0.007284608,0.001332803,0.00005199122,0.0002716658,0.02320591,0.001848142,0.0004131744,0.06612265,0.8990788,0.0002696849],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01314315,0.005440923,0.007624671,0.6460468,0.004723452,0.0004865832,0.0008769145,0.0003288523,0.3213287],"genre_scores_gemma":[0.4641115,0.009360989,0.03495745,0.3124249,0.001114115,0.0007637538,0.001630258,0.0005133981,0.1751236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1647127,"threshold_uncertainty_score":0.9688148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01123725764124003,"score_gpt":0.1839519966232134,"score_spread":0.1727147389819734,"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."}}