{"id":"W6950440756","doi":"10.5281/zenodo.7405478","title":"Lerneca inalata subsp. beripocone Lima 2016","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Phytochemistry Medicinal Plant Applications","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"State (computer science); Work (physics); Population; Quarter (Canadian coin)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001686401,0.0003877401,0.0004946855,0.0006873957,0.0009850477,0.0005970505,0.000471811,0.00037928,0.01029959],"category_scores_gemma":[0.0002132358,0.0001566135,0.0002873755,0.0004969974,0.0002716051,0.0006626627,0.0005075923,0.0006083959,0.004712649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007775301,"about_ca_system_score_gemma":0.0003689817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007575556,"about_ca_topic_score_gemma":0.01738307,"domain_scores_codex":[0.9998598,0.00001136564,0.00001076716,0.00006461159,0.00002777437,0.00002569831],"domain_scores_gemma":[0.9998717,0.00002697053,0.00002206771,0.00001698355,0.00003309408,0.00002907811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001208721,0.0002619707,0.03158674,0.001486524,0.00008842157,0.003464168,0.002473498,0.0005605741,0.6140763,0.001739869,0.007544199,0.335509],"study_design_scores_gemma":[0.00006527325,0.0006456695,0.6146234,0.0002705055,0.0001972667,0.006387763,0.002445899,0.0005321303,0.03309489,0.0005770628,0.3411056,0.0000544443],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6528055,0.007582749,0.004341681,0.0005291709,0.0002289302,0.0002831197,0.007731878,0.0007324393,0.3257645],"genre_scores_gemma":[0.9278701,0.001303444,0.003659304,0.000517396,0.00004277873,0.0001731338,0.01013437,0.00008552929,0.05621396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01029959,"threshold_uncertainty_score":0.0344556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03696570248394457,"score_gpt":0.219193532266996,"score_spread":0.1822278297830514,"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."}}