{"id":"W2972773739","doi":"10.32622/ijrat.742019202","title":"Phytochemical Screening of Murraya koenigii (L.) Spreng","year":2019,"lang":"en","type":"article","venue":"International Journal of Research in Advent Technology","topic":"Morinda citrifolia extract uses","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Murraya; Phytochemical; Traditional medicine; Chemistry; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001215577,0.00008897286,0.000349937,0.002760442,0.000009899985,0.000008891715,0.0006693836,0.000186357,0.0002682167],"category_scores_gemma":[0.001101762,0.00007831034,0.000128503,0.0006107036,0.0002182189,0.0001226075,0.0002077082,0.001368995,0.00002954257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002101426,"about_ca_system_score_gemma":0.0002448641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001731002,"about_ca_topic_score_gemma":0.00000249737,"domain_scores_codex":[0.9974225,0.00006041521,0.0006651158,0.0001597105,0.001400091,0.0002921376],"domain_scores_gemma":[0.9978088,0.0002773721,0.0002709627,0.0002338087,0.001323135,0.00008599546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001646747,0.0008352149,0.626289,0.0001149864,0.0003431128,0.001520385,0.00009398963,0.00007177337,0.3143287,0.006903206,0.0007901783,0.04706274],"study_design_scores_gemma":[0.01267567,0.002945832,0.1108058,0.006213411,0.00003822817,0.005692325,0.001552145,0.0007995781,0.7974289,0.01352637,0.04803367,0.0002880642],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989189,0.0005707581,0.0003954073,0.007201773,0.0003533713,0.000217688,0.000003334254,0.00001689104,0.002051742],"genre_scores_gemma":[0.9937709,0.0001882001,0.005591097,0.00003163072,0.0001963759,0.0000050707,0.000002017167,0.00001427285,0.0002004462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5154831,"threshold_uncertainty_score":0.5947678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05623743556544201,"score_gpt":0.4473415567138688,"score_spread":0.3911041211484268,"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."}}