{"id":"W7042795020","doi":"","title":"Quantifying spatiotemporal variability in mesozooplankton distribution and nutritional quality around seamounts within the Canadian Offshore Pacific Bioregion","year":2023,"lang":"en","type":"dissertation","venue":"UVic’s Research and Learning Repository (University of Victoria)","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Zooplankton; Biomass (ecology); Bioregion; Copepod; Seamount; Trophic level; Marine ecosystem; Submarine pipeline; Ecosystem","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003843635,0.0002964454,0.0002734324,0.001919957,0.001492581,0.0009448729,0.0007395924,0.000257719,0.0006151842],"category_scores_gemma":[0.001031447,0.0001941857,0.0003891783,0.003658708,0.0004217077,0.0002632383,0.0006581302,0.0002867329,0.0001235022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007115019,"about_ca_system_score_gemma":0.008487623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9704341,"about_ca_topic_score_gemma":0.9900539,"domain_scores_codex":[0.9995871,0.00001429767,0.00002049817,0.0001122198,0.0001637503,0.0001021963],"domain_scores_gemma":[0.9989246,0.00005276673,0.0001978057,0.00004250512,0.0006693883,0.0001129809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000033695,0.00001161551,0.9857587,0.00003417728,0.00008677868,0.00006020731,0.00145344,0.0003199122,0.001876762,0.00007260504,0.0009512899,0.009341006],"study_design_scores_gemma":[3.720963e-7,0.000002032762,0.9988567,0.000008461931,0.000009715122,0.0000059848,0.0005893214,0.0001283803,0.00006722327,0.000003396907,0.0003259486,0.000002654348],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962328,0.0001846422,0.000138014,0.00005252842,0.000003784886,0.00001740211,0.002043397,0.00001187454,0.001315448],"genre_scores_gemma":[0.9944365,0.0003898533,0.0006101272,0.00004512625,0.000003627523,0.00003321821,0.003504234,0.000008265,0.0009690071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02956593,"threshold_uncertainty_score":0.05948007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04071782349745492,"score_gpt":0.2728255312020255,"score_spread":0.2321077077045706,"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."}}