{"id":"W4317881316","doi":"10.33425/2833-0307.1005","title":"Nutritional, Phytochemical and Carbohydrate Profile of Giant Swamp Taro [Cyrtosperma merkusii (Hassk.). Schott]","year":2022,"lang":"en","type":"article","venue":"Endocrinology Metabolism and Nutrition","topic":"Food and Agricultural Sciences","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Nutrition, Metabolism and Diabetes","funders":"","keywords":"Colocasia esculenta; Phytochemical; Food science; Biology; Starch; Amylose; Horticulture; Crop; Carotenoid; Nutrient; Botany; Chemistry; Agronomy","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":[0.00004756765,0.0002859061,0.0002216637,0.0004682064,0.0003088538,0.0002316323,0.0001055433,0.0001614646,0.0008867887],"category_scores_gemma":[0.00007287692,0.0001124549,0.0001653512,0.0003918062,0.0001825599,0.0002317169,0.0001777641,0.0002821825,0.0001553308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609417,"about_ca_system_score_gemma":0.0001181684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00500492,"about_ca_topic_score_gemma":0.009622168,"domain_scores_codex":[0.9999719,0.00000291467,0.000002495714,0.000009716234,0.000007052396,0.000005981508],"domain_scores_gemma":[0.9999222,0.000007478753,0.00001960778,0.000003802287,0.00001414549,0.00003280705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007625087,0.0002977448,0.02040842,0.0001321578,0.00004197739,0.0005654683,0.0003768924,0.00007607571,0.973792,0.00004726122,0.00007546051,0.003423954],"study_design_scores_gemma":[0.00002066622,0.001337302,0.9685717,0.0000135841,0.00007269342,0.0005783453,0.0006460455,0.0004684329,0.02709916,0.0000593868,0.001108215,0.00002443581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995671,0.0000895548,0.00003975244,0.000007290874,0.000001163487,0.000003216355,0.0001222485,0.000002786722,0.0001668012],"genre_scores_gemma":[0.9976903,0.0001190164,0.0002722926,0.00002942576,0.000001955613,0.000007209014,0.0006891474,0.000006249935,0.001184436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00500492,"threshold_uncertainty_score":0.009951532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200235724814994,"score_gpt":0.2087526224631903,"score_spread":0.1967502652150404,"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."}}