{"id":"W2682060310","doi":"10.1016/b978-0-08-100664-1.00005-3","title":"Marine and Aquatic Sciences Information Literacy","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Information literacy; Multidisciplinary approach; Government (linguistics); Encyclopedia; Library science; Literacy; Field (mathematics); Public relations; Political science; Knowledge management; Data science; Sociology; Computer science; Social science; Pedagogy","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":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000588168,0.0007101277,0.0005893225,0.002685419,0.0009359684,0.005731573,0.0005584049,0.001171399,0.4301281],"category_scores_gemma":[0.00173932,0.0002807324,0.0002867808,0.003336154,0.0008593431,0.005804629,0.003093242,0.001405667,0.190511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001158132,"about_ca_system_score_gemma":0.002215022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003581689,"about_ca_topic_score_gemma":0.008243813,"domain_scores_codex":[0.9996786,0.00003629065,0.00002397924,0.00004199723,0.0001816257,0.00003752894],"domain_scores_gemma":[0.9993747,0.0002067569,0.00003157136,0.00008268687,0.0001867533,0.000117472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001587755,0.00002320618,0.0001708822,0.0002842645,0.000003224452,0.00007192249,0.0003240679,0.0001126942,0.0005550545,0.02829969,0.4933681,0.476771],"study_design_scores_gemma":[9.529915e-7,0.000003078965,0.0001392238,0.0001304879,0.000001120669,0.00003363726,0.00005828694,0.00003221978,0.00005924216,0.00274743,0.9967924,0.00000182463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.0004961894,0.006004556,0.001048852,0.00193119,0.001306682,0.00001500202,0.0005170375,0.0002617676,0.9884186],"genre_scores_gemma":[0.001393696,0.003581726,0.0004792664,0.0003902018,0.0002603003,0.00001116075,0.0003349312,0.0001046435,0.9934441],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9942684,"threshold_uncertainty_score":0.812853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088206691095427,"score_gpt":0.2375106632352495,"score_spread":0.2266285963242952,"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."}}