{"id":"W4221045427","doi":"10.3897/bdj.10.e76050","title":"Toward an atlas of Salish Sea biodiversity: the flora and fauna of Galiano Island, British Columbia, Canada. Part I. Marine zoology","year":2022,"lang":"en","type":"article","venue":"Biodiversity Data Journal","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Royal British Columbia Museum; Precision Nanosystems (Canada); Coquitlam College; University of Victoria; University of British Columbia","funders":"","keywords":"Biodiversity; Citizen science; Fauna; Global biodiversity; Amateur; Marine biodiversity; Species richness; Complementarity (molecular biology)","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":[0.0007382921,0.0007683383,0.0003429112,0.01560416,0.002483335,0.002362535,0.00120717,0.0003828776,0.00922996],"category_scores_gemma":[0.001933291,0.0003059568,0.000316975,0.02766961,0.0007176819,0.0008157328,0.001394878,0.0009305248,0.001682036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02758559,"about_ca_system_score_gemma":0.05419603,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.992076,"about_ca_topic_score_gemma":0.9973971,"domain_scores_codex":[0.9994144,0.00003560729,0.00004437907,0.0000909584,0.0002976856,0.0001169424],"domain_scores_gemma":[0.9963888,0.0001207073,0.0003221287,0.0001261421,0.00245488,0.0005873322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001398727,0.00006582237,0.3438385,0.003069199,0.0001559061,0.0004722918,0.00639612,0.001535132,0.004914865,0.003620207,0.3366854,0.2991067],"study_design_scores_gemma":[0.00001145937,0.00001157646,0.7986364,0.0005725469,0.00003368705,0.00009821351,0.003149965,0.0002829357,0.0001591935,0.0003011209,0.196715,0.00002803512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2392579,0.03355171,0.004233401,0.006316399,0.0005091074,0.0009071804,0.6181979,0.001441996,0.09558442],"genre_scores_gemma":[0.4362955,0.02939717,0.05038742,0.001926697,0.0002009897,0.001300519,0.4106141,0.0004473702,0.06943019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02758559,"threshold_uncertainty_score":0.2001485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555114621566904,"score_gpt":0.1840606351216555,"score_spread":0.1585094889059865,"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."}}