{"id":"W2995702596","doi":"10.1111/ddi.13013","title":"Seafloor biodiversity of Canada's three oceans: Patterns, hotspots and potential drivers","year":2019,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University; Bedford Institute of Oceanography; Memorial University of Newfoundland; Université Laval; Fisheries and Oceans Canada; Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Science and Technology, Taiwan","keywords":"Benthic zone; Oceanography; Arctic; Environmental science; Biodiversity; Ecology; Species diversity; Intertidal zone; Geography; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004201665,0.0003859262,0.0004032703,0.002481918,0.001653406,0.00179406,0.0006983855,0.0003181909,0.001229381],"category_scores_gemma":[0.0009779288,0.0002552253,0.0005655174,0.005319802,0.001030309,0.0003815264,0.001201064,0.000364388,0.00008122717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007014661,"about_ca_system_score_gemma":0.009659842,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9639223,"about_ca_topic_score_gemma":0.9835004,"domain_scores_codex":[0.9995222,0.00003339905,0.00002806694,0.0001152181,0.0001230622,0.000177936],"domain_scores_gemma":[0.998325,0.0001300917,0.0004327486,0.00005693526,0.0006224203,0.0004327651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002237942,0.00000407096,0.9962458,0.00002287186,0.00007250875,0.00002551256,0.0002858687,0.00006962587,0.0001829355,0.0000777763,0.0001828628,0.002807752],"study_design_scores_gemma":[0.000001120907,0.000003225243,0.9989586,0.0000162641,0.00001294067,0.00001402007,0.0005966208,0.000101391,0.00002189811,0.00001971641,0.0002511326,0.000003065477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949619,0.001103383,0.00007401765,0.0002190069,0.000005149862,0.000007598114,0.002499021,0.000009535708,0.001120322],"genre_scores_gemma":[0.9986492,0.0003621297,0.0001016857,0.00002815852,0.000003398593,0.000003343172,0.0006896345,0.000002605453,0.0001598563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03607768,"threshold_uncertainty_score":0.07258022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008856953173322142,"score_gpt":0.16947684006601,"score_spread":0.1606198868926879,"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."}}