{"id":"W4389543861","doi":"10.23919/oceans52994.2023.10337010","title":"Harnessing Technologies for Monitoring Pacific Conservation Areas: From Sea Floor to Sky","year":2023,"lang":"en","type":"article","venue":"","topic":"Marine Ecology and Invasive Species","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Seamount; Marine protected area; Habitat; Environmental resource management; Oceanography; Fishery; Marine habitats; Remotely operated underwater vehicle; Environmental science; Geography; Ecology; Computer science; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001089105,0.0004425803,0.0002548956,0.002676893,0.0005930595,0.001900399,0.0007346366,0.0005586016,0.002019964],"category_scores_gemma":[0.001380777,0.0002969862,0.0002330556,0.002524716,0.0006352987,0.001807733,0.001807042,0.000970754,0.0006838793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006624266,"about_ca_system_score_gemma":0.001168115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01991307,"about_ca_topic_score_gemma":0.05638982,"domain_scores_codex":[0.9990895,0.0001484152,0.00002311976,0.0001320754,0.0005497201,0.00005720574],"domain_scores_gemma":[0.9989727,0.0001844868,0.0001260626,0.00009520251,0.0005333549,0.00008821047],"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":[0.00005575141,0.00005272783,0.0692569,0.0005408518,0.00009333311,0.0002162193,0.0009385814,0.002162908,0.07257976,0.002906946,0.008625179,0.8425708],"study_design_scores_gemma":[0.00006097134,0.0006760426,0.3657325,0.001407033,0.0005135685,0.002889282,0.01197506,0.03898478,0.1354153,0.02881682,0.4131985,0.0003302234],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2313225,0.02430719,0.5941312,0.008282913,0.0006991801,0.0006415866,0.006198148,0.003897856,0.1305194],"genre_scores_gemma":[0.4171863,0.01436145,0.5521564,0.00215986,0.0002629005,0.0003374927,0.001927383,0.0002975098,0.01131077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01991307,"threshold_uncertainty_score":0.03959435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601891828477016,"score_gpt":0.2502944915945507,"score_spread":0.2242755733097805,"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."}}