{"id":"W4238871958","doi":"10.1515/iupac.78.0357","title":"HPTLC","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Computer science; Chemical nomenclature; Relation (database); Data science; Management science; Environmental chemistry; Chemistry; Engineering; Data mining; Linguistics","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":[0.001370062,0.002389794,0.001595464,0.005640133,0.001076015,0.003185386,0.003705337,0.00223897,0.1393692],"category_scores_gemma":[0.008560232,0.0007122437,0.001617746,0.008970266,0.0004861273,0.002496034,0.002124087,0.00238447,0.1692854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002109417,"about_ca_system_score_gemma":0.003854871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02504344,"about_ca_topic_score_gemma":0.04415721,"domain_scores_codex":[0.9984114,0.0002555511,0.000260277,0.0005206154,0.0003846548,0.0001674026],"domain_scores_gemma":[0.9968908,0.00107142,0.0003964493,0.0006302201,0.0008138522,0.0001972953],"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":[0.00008986111,0.00001886209,0.0006875473,0.001818219,0.00003928149,0.00002962491,0.00002789531,0.00028576,0.0001822467,0.0008825883,0.9910228,0.004915251],"study_design_scores_gemma":[0.0001423929,0.00001447736,0.001695268,0.000562201,0.0000308261,0.00004893063,0.00003826336,0.0002306709,0.0002369646,0.001515343,0.9954605,0.0000241702],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004783168,0.0000945893,0.00009603563,0.00005088287,0.00001268709,0.00001261087,0.9986755,0.0003245455,0.000685269],"genre_scores_gemma":[0.0001623229,0.0001062046,0.00032504,0.0000678455,0.000004928933,0.00008227787,0.9986396,0.00008339013,0.0005283725],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8606308,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009668173750086757,"score_gpt":0.3657987946835715,"score_spread":0.3561306209334847,"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."}}