{"id":"W2111210614","doi":"10.1371/journal.pone.0113171","title":"Estimating Trans-Seasonal Variability in Water Column Biomass for a Highly Migratory, Deep Diving Predator","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Antarctic Division; Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Pelagic zone; Water column; Phytoplankton; Environmental science; Foraging; Context (archaeology); Oceanography; Chlorophyll a; SeaWiFS; Ecology; Biology; Geology; Nutrient","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003620531,0.0002750157,0.0002448887,0.001026609,0.0002699469,0.0003561263,0.0002053585,0.0002024544,0.0003601443],"category_scores_gemma":[0.0007134179,0.0002427773,0.000244284,0.0004136977,0.0001319775,0.0003644641,0.0003411082,0.0001307732,0.0001538388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002527252,"about_ca_system_score_gemma":0.0001657648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008710388,"about_ca_topic_score_gemma":0.02957639,"domain_scores_codex":[0.9999198,0.000008799766,0.000007924463,0.0000387788,0.00001334703,0.00001147218],"domain_scores_gemma":[0.9996789,0.00006505889,0.0001440166,0.00002501669,0.00005793459,0.00002919737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003273878,0.00001676246,0.9849904,0.00001121248,0.00004612692,0.00003202776,0.0001093684,0.0005598447,0.006821729,0.00001122707,0.00003523141,0.007333367],"study_design_scores_gemma":[0.000002776276,0.0000670862,0.9933515,0.000005050012,0.00002397879,0.00006472589,0.0001562822,0.005350193,0.000816948,0.00001834311,0.0001393147,0.000003827233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993435,0.00003277134,0.0004473738,0.000003207143,8.929761e-7,0.000003160066,0.00008111357,0.000006857419,0.00008129967],"genre_scores_gemma":[0.9966287,0.00006157588,0.002710069,0.00000463475,0.000002726074,0.000009542596,0.0004270009,0.000004094102,0.0001516151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008710388,"threshold_uncertainty_score":0.01731938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374301548597663,"score_gpt":0.2142735196517589,"score_spread":0.1905305041657822,"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."}}