{"id":"W3133618427","doi":"","title":"Phytochemical Composition, Gas Chromatography-Mass Spectrometric (GC-MS) Analysis and Anti-Bacterial Activity of Ethanol Leaf-Extract of Ageratum conyzoides","year":2016,"lang":"en","type":"article","venue":"Journal of Basic & Applied Sciences","topic":"Medicinal Plant Research","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ageratum conyzoides; Phytochemical; Antimicrobial; Terpenoid; Traditional medicine; Antibacterial activity; Chemistry; Gas chromatography; Gas chromatography–mass spectrometry; Biology; Chromatography; Food science; Botany; Microbiology; Bacteria; Medicine; Mass spectrometry; Weed","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008900748,0.0003537639,0.0002797326,0.0005455943,0.0001831501,0.0001215507,0.00008666478,0.0001506639,0.001040805],"category_scores_gemma":[0.00007892054,0.00006775603,0.000180977,0.0004079647,0.0001095064,0.0002004579,0.0001088104,0.0002218589,0.0001437104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618698,"about_ca_system_score_gemma":0.0002241384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001786145,"about_ca_topic_score_gemma":0.00277503,"domain_scores_codex":[0.9999403,0.000006617446,0.000007522967,0.0000175602,0.00001744221,0.00001059561],"domain_scores_gemma":[0.9999324,0.00001197198,0.00002160732,0.000005979059,0.00001823021,0.000009811601],"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":[0.0001474399,0.00004117599,0.002125775,0.0001130591,0.000007223046,0.0000827458,0.00002145959,0.00004990465,0.9938764,0.00001475016,0.00001950615,0.003500652],"study_design_scores_gemma":[0.00004237546,0.001537653,0.2399001,0.00005776824,0.0001497886,0.001054746,0.0002186412,0.0006521885,0.749407,0.0001234639,0.006828156,0.00002810244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922177,0.00382045,0.001444056,0.00006859544,0.00001299487,0.00004297918,0.001327567,0.00004566932,0.001020041],"genre_scores_gemma":[0.9902526,0.001868172,0.004220015,0.0001022907,0.00001298686,0.00004647602,0.001274302,0.00001200499,0.002211185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001786145,"threshold_uncertainty_score":0.003551543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045488872864138,"score_gpt":0.2574187587901213,"score_spread":0.2369638700614799,"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."}}