{"id":"W4408989344","doi":"10.1101/2025.03.26.645521","title":"The nutritional value of invertebrate aquatic foods","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University","funders":"","keywords":"Invertebrate; Value (mathematics); Fishery; Environmental science; Business; Biology; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002181075,0.0001843701,0.0001448954,0.0008975834,0.0003370521,0.0008742607,0.0001110556,0.0001893838,0.002102728],"category_scores_gemma":[0.0004735204,0.00006996998,0.0001023121,0.001025008,0.0003396907,0.0002238035,0.0004667012,0.0001425947,0.0004588407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000377785,"about_ca_system_score_gemma":0.0001919632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005195927,"about_ca_topic_score_gemma":0.009337765,"domain_scores_codex":[0.9998575,0.00002779259,0.000008341282,0.00004245529,0.0000473376,0.00001654644],"domain_scores_gemma":[0.9997373,0.00004301313,0.00008556507,0.0000193792,0.00007135388,0.00004331094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005436888,0.00006264085,0.7841893,0.0003883286,0.0002544505,0.0003792455,0.0005704382,0.001330528,0.1248815,0.002039473,0.00118565,0.08417469],"study_design_scores_gemma":[0.000002841051,0.00009128865,0.9869114,0.00006270683,0.00003819256,0.0002583828,0.0006029874,0.0006730968,0.006035149,0.001502446,0.003813221,0.000008239776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901571,0.001043719,0.0005402844,0.0001349723,0.000008933111,0.000003970559,0.00101549,0.00001139658,0.007084098],"genre_scores_gemma":[0.997005,0.0005987358,0.0006452602,0.00004133197,0.00000573619,0.00000367683,0.0004298778,0.000005408566,0.001264983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005195927,"threshold_uncertainty_score":0.01033133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153137148084818,"score_gpt":0.2123845427102193,"score_spread":0.1970708279017374,"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."}}