{"id":"W7096548958","doi":"","title":"Abstract On Writing OpenMath Content Dictionaries","year":2008,"lang":"en","type":"article","venue":"","topic":"Hibiscus Plant Research Studies","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Content (measure theory); Content analysis; Key (lock); Semantics (computer science)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004607448,0.0001515493,0.0001871361,0.00008055638,0.0008651012,0.0000148582,0.0001681227,0.0001211969,0.003913305],"category_scores_gemma":[0.0001947521,0.0001130185,0.00006559835,0.00009054402,0.0003105068,0.0001061996,0.0000858565,0.000675335,0.001419941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005519975,"about_ca_system_score_gemma":0.00006146246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005515133,"about_ca_topic_score_gemma":0.00003182066,"domain_scores_codex":[0.9987559,0.0001082499,0.000242567,0.0002271532,0.0002381421,0.0004279691],"domain_scores_gemma":[0.9987999,0.0007763246,0.00004696993,0.0001137836,0.00009810273,0.0001649686],"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":[0.001500043,0.001722655,0.2455898,0.0001197169,0.001007339,0.002142368,0.003394975,0.0005207889,0.07320731,0.04780181,0.6034471,0.01954609],"study_design_scores_gemma":[0.002462701,0.0003347773,0.2958378,0.00003485769,0.00003333216,0.0002556793,0.00118881,0.0003550805,0.05434636,0.0001724691,0.6445199,0.0004582603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7790049,0.0002428395,0.00001542641,0.002468325,0.0003403296,0.0002677163,0.00005274294,0.0001551729,0.2174526],"genre_scores_gemma":[0.9855111,0.000594676,0.00007879224,0.001705132,0.0002019653,0.00004802113,0.0000185568,0.00001068658,0.0118311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2065062,"threshold_uncertainty_score":0.9993576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5041074565717184,"score_gpt":0.4977632008820969,"score_spread":0.006344255689621492,"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."}}