{"id":"W7000995533","doi":"","title":"Human Nutraceutical Research Unit: Advancing Foods & Natural Health Products","year":2011,"lang":"en","type":"other","venue":"The Atrium (University of Guelph)","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Directorate for Biological Sciences; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Government (linguistics); Event (particle physics); General partnership; Nutraceutical; Human health; Public health; Natural (archaeology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002727633,0.0009214525,0.0008321949,0.002293737,0.001581407,0.004392699,0.001057162,0.002019824,0.3462206],"category_scores_gemma":[0.001902876,0.0003087687,0.0003593205,0.00291736,0.0008529571,0.002080668,0.001606933,0.001938519,0.177977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001889339,"about_ca_system_score_gemma":0.004863495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004728708,"about_ca_topic_score_gemma":0.0188248,"domain_scores_codex":[0.9991264,0.0001012739,0.00003669226,0.0001756787,0.0004298711,0.0001301824],"domain_scores_gemma":[0.9972413,0.0002797291,0.0001036339,0.000129374,0.001067692,0.001178253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008605554,0.0001312413,0.0002122557,0.0004787947,0.000003852363,0.00009334401,0.0001094703,0.00002346251,0.002347977,0.003930935,0.7251872,0.2673954],"study_design_scores_gemma":[0.000009974782,0.00009314901,0.0008156136,0.0001061961,0.000003989987,0.00007081384,0.00007169355,0.00002776534,0.0007917564,0.0006406409,0.9973639,0.000004521265],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001918163,0.03458738,0.002370561,0.02229294,0.008207021,0.0006948228,0.00315564,0.000996564,0.9257769],"genre_scores_gemma":[0.004274652,0.0187566,0.001962343,0.002431753,0.001808099,0.0001508478,0.001267054,0.0001507166,0.969198],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3462206,"threshold_uncertainty_score":0.932537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09437025400874678,"score_gpt":0.3568436063954481,"score_spread":0.2624733523867013,"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."}}