{"id":"W4250226751","doi":"10.1515/iupac.85.0325","title":"Array Detector","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Terminology; Chemical nomenclature; Mass spectrometry; Standardization; Chemistry; Accelerator mass spectrometry; Tandem mass spectrometry; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001460729,0.00034598,0.0003714313,0.0001642433,0.00004626239,0.00004208925,0.0002553764,0.0003407471,0.002537968],"category_scores_gemma":[0.0001108794,0.0002725073,0.0001043871,0.0001314973,0.00004685954,0.00008126051,0.00002221215,0.0002936929,0.000008916669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002786185,"about_ca_system_score_gemma":0.0001191349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008622925,"about_ca_topic_score_gemma":0.000118612,"domain_scores_codex":[0.9986768,0.00002315972,0.0002914861,0.0002374547,0.0004504965,0.0003205371],"domain_scores_gemma":[0.9991511,0.00003663729,0.00005860267,0.0004703271,0.0001646092,0.0001187816],"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":[0.0000208652,0.00001655244,6.750969e-7,0.0001051376,0.00005729462,0.00001503528,0.000003966242,0.0001464607,0.0002199823,0.000001013903,0.9979044,0.001508644],"study_design_scores_gemma":[0.0003551339,0.00004822126,0.000003261723,0.0002190208,0.00005005056,0.000006165518,0.00000421942,0.0003987108,0.0001709963,0.00002268234,0.9983491,0.0003724453],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000005204629,0.0007871149,0.06901013,0.00003691983,0.0009565608,0.0001514844,0.9286874,0.0002943834,0.00007080365],"genre_scores_gemma":[0.00002747567,0.001728054,0.0003112033,0.00006419005,0.0008360147,0.00001061483,0.9967228,0.00006905293,0.00023066],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06869893,"threshold_uncertainty_score":0.9999727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009058199715292552,"score_gpt":0.3176296563050507,"score_spread":0.3085714565897582,"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."}}