{"id":"W6950107397","doi":"10.5281/zenodo.4606559","title":"Aquatic biodiversity enhances multiple nutritional benefits to humans","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cardiac Fibrosis and Remodeling","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biodiversity; Species richness; Ecosystem; Ecological health; Biomass (ecology); Sustainability; Micronutrient; Ecosystem services; Aquatic ecosystem","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":[0.0004856527,0.0002764082,0.0005140067,0.001268744,0.0003843183,0.001070721,0.0001763369,0.0002411995,0.003999057],"category_scores_gemma":[0.001495151,0.0001353715,0.000399679,0.0016783,0.0006042652,0.0007123978,0.001632224,0.0002511684,0.0006395698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003697378,"about_ca_system_score_gemma":0.0003130405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002550307,"about_ca_topic_score_gemma":0.005954721,"domain_scores_codex":[0.9994825,0.0001518778,0.00003484863,0.0001910767,0.00009057324,0.00004916179],"domain_scores_gemma":[0.9993863,0.0001819038,0.0002302108,0.00008648256,0.00005777509,0.00005729575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004986452,0.00009327525,0.6985455,0.002694896,0.00110941,0.0004857595,0.0008937118,0.007543063,0.02503879,0.006327453,0.006148892,0.2506207],"study_design_scores_gemma":[0.000009254545,0.0000685945,0.9717324,0.0001412455,0.0001272029,0.0003034748,0.0004277992,0.00189967,0.0009912783,0.007906432,0.01636776,0.00002499406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564595,0.005254645,0.009633007,0.0005454849,0.0000383076,0.00003204284,0.01708285,0.0001334047,0.01082075],"genre_scores_gemma":[0.9806325,0.002097907,0.007785162,0.0002259694,0.00004851191,0.00004244626,0.008157068,0.0000395446,0.0009709621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003999057,"threshold_uncertainty_score":0.01337814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04786819569380909,"score_gpt":0.2578558825084306,"score_spread":0.2099876868146215,"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."}}