{"id":"W4247464031","doi":"10.1515/iupac.79.2002","title":"Sensitivity (in Metrology and Analytical Chemistry)","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; CAS Registry Number; Hazard; Computer science; Toxicology; Chemistry; Philosophy; Organic chemistry; Biology; 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":[],"consensus_categories":[],"category_scores_codex":[0.002635405,0.002643449,0.001974405,0.006066745,0.0008208937,0.004167354,0.002943283,0.002076907,0.1075486],"category_scores_gemma":[0.01928533,0.0009079255,0.003091352,0.008945147,0.0005608313,0.002878953,0.002837284,0.002516014,0.1324054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165071,"about_ca_system_score_gemma":0.002954961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01134655,"about_ca_topic_score_gemma":0.01656371,"domain_scores_codex":[0.9957981,0.0007758107,0.0007712147,0.001350066,0.001011757,0.0002930035],"domain_scores_gemma":[0.9912546,0.003366269,0.001154964,0.002114717,0.001760736,0.0003487838],"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":[0.0001422545,0.0000264496,0.002459125,0.003000325,0.0001241789,0.000024373,0.0000231505,0.0004598763,0.0001426162,0.0008910104,0.9822723,0.01043434],"study_design_scores_gemma":[0.0002139077,0.00002652214,0.006140551,0.0007605751,0.00007854176,0.00008514034,0.00004181769,0.0003357042,0.0003645876,0.002163468,0.989748,0.00004123137],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001152761,0.0003168744,0.000146277,0.00006758565,0.00005081108,0.00001658682,0.9979335,0.0003401854,0.001012786],"genre_scores_gemma":[0.0006270087,0.0002645502,0.0006252025,0.0001371941,0.00002648856,0.0001283301,0.9971544,0.0001089424,0.0009277916],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1075486,"threshold_uncertainty_score":0.3597859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01175363032226209,"score_gpt":0.3749871227748649,"score_spread":0.3632334924526028,"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."}}