{"id":"W4233487884","doi":"10.1515/iupac.76.0402","title":"Threshold","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Hazard; Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; Biology; Linguistics; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00138202,0.002200823,0.001525674,0.004463432,0.001203593,0.004305144,0.003089316,0.002104276,0.1475],"category_scores_gemma":[0.0140322,0.0007472126,0.002026908,0.006197014,0.0004443317,0.003705684,0.002528607,0.002173869,0.1983373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001876642,"about_ca_system_score_gemma":0.002740994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01648464,"about_ca_topic_score_gemma":0.03651229,"domain_scores_codex":[0.99755,0.0003833628,0.0004017813,0.0009351543,0.0004817631,0.0002480041],"domain_scores_gemma":[0.9958155,0.001380266,0.0003646174,0.001173016,0.001045074,0.0002215288],"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":[0.00007007418,0.00001976848,0.0009779773,0.0008050469,0.00002887447,0.000024202,0.00003425114,0.0002830955,0.00009643593,0.001025071,0.989254,0.007381252],"study_design_scores_gemma":[0.0001028384,0.00001808491,0.002460949,0.0005059225,0.00003105382,0.00009178508,0.0001125319,0.0006182151,0.0002666752,0.004267269,0.9914885,0.000036286],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001918485,0.0001837959,0.0002961128,0.0001410925,0.00005763727,0.00003295358,0.9958677,0.0007817761,0.002447116],"genre_scores_gemma":[0.0004914561,0.0001218914,0.0008089311,0.0001284741,0.00001284699,0.0001436431,0.9966587,0.0001729578,0.001461022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8525,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204179899693156,"score_gpt":0.4171378161450166,"score_spread":0.396719826175701,"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."}}