{"id":"W3125513283","doi":"10.3354/esep00196","title":"Making ocean literacy inclusive and accessible","year":2021,"lang":"en","type":"article","venue":"Ethics in Science and Environmental Politics","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Dalhousie University","funders":"Natural Environment Research Council; Global Challenges Research Fund; Sight Research UK; Canada First Research Excellence Fund; UK Research and Innovation; Ocean Frontier Institute; Society for Conservation Biology","keywords":"Literacy; Indigenous; Privilege (computing); Variety (cybernetics); Citizen science; Political science; Public relations; Sociology; Ecology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007656483,0.0001197102,0.0001003197,0.00005759479,0.000452833,0.0001669544,0.0001982675,0.0000559451,0.0002224335],"category_scores_gemma":[0.000156599,0.0001169881,0.00001338846,0.0002974672,0.001638816,0.0005991029,0.007298409,0.0003299261,0.00002185049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002739401,"about_ca_system_score_gemma":0.00004917074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001734767,"about_ca_topic_score_gemma":0.000106805,"domain_scores_codex":[0.998358,0.00004008607,0.0001691875,0.0004454124,0.0006012396,0.0003861359],"domain_scores_gemma":[0.9995307,0.00009040839,0.00003795724,0.000201883,0.000005152205,0.0001339411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001372847,0.0004965714,0.6491711,0.0001418063,0.00001175973,0.0004305434,0.02834744,0.0004788276,0.0177887,0.06731876,0.0007232273,0.2350775],"study_design_scores_gemma":[0.0008943309,0.0001267566,0.6370234,0.0001240342,0.00002674575,0.0001628731,0.01110981,0.006522949,0.005845548,0.2787533,0.05853382,0.0008764449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9464549,0.0001204885,0.00007471913,0.004042526,0.00009790515,0.0001010132,0.000009459002,0.00001217517,0.0490868],"genre_scores_gemma":[0.9943612,0.0003831588,0.001220523,0.003011167,0.0000237824,0.000002218061,0.000003755593,0.000006723275,0.0009874881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2342011,"threshold_uncertainty_score":0.9096946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880819080790718,"score_gpt":0.3313855785304162,"score_spread":0.302577387722509,"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."}}