{"id":"W2741890902","doi":"10.1002/ecs2.1884","title":"Quantifying marine mammal hotspots in British Columbia, Canada","year":2017,"lang":"en","type":"article","venue":"Ecosphere","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Raincoast Conservation Foundation; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Raincoast Conservation Foundation; International Fund for Animal Welfare","keywords":"Geography; Marine mammal; Hotspot (geology); Marine protected area; Marine conservation; Biodiversity hotspot; Ecology; Biodiversity; Spatial ecology; Wildlife; Environmental resource management; Habitat; Environmental science; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001277129,0.000080924,0.000176331,0.000001391306,0.0004195027,0.0002688275,0.0004662297,0.00003521649,0.05553742],"category_scores_gemma":[0.00008747115,0.000135969,0.00003000938,0.00005382849,0.00007040903,0.000187504,0.001203112,0.0001281786,0.0003945754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003296318,"about_ca_system_score_gemma":0.00003542014,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9994695,"about_ca_topic_score_gemma":0.9999977,"domain_scores_codex":[0.9989471,0.00001704219,0.0001729942,0.0002976846,0.0002249266,0.0003402168],"domain_scores_gemma":[0.9994369,0.00001699773,0.00009596183,0.0003646368,0.000004451904,0.00008104488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001841574,0.00001562679,0.8160403,0.00001014089,0.000003776526,0.0002073821,0.000005534985,0.000006345932,0.000003195875,0.000001769384,0.09916656,0.08453752],"study_design_scores_gemma":[0.0002216778,0.0000160698,0.906129,0.00001940775,0.000002792853,0.00001066671,0.00003499987,0.00008186005,0.000001960719,0.00004413916,0.09328505,0.000152374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7415612,0.00005934409,3.122772e-7,0.0001348119,0.0001273048,0.0001035551,0.000005505741,0.00001054512,0.2579975],"genre_scores_gemma":[0.9865949,0.0001185407,0.000309519,0.0002522114,0.00003674197,0.00001347102,0.000001903771,0.0000139095,0.0126588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2453386,"threshold_uncertainty_score":0.945326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180260490617333,"score_gpt":0.2232647030485158,"score_spread":0.2052386539867825,"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."}}