{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001525606,0.001917421,0.001568567,0.003110858,0.0009956596,0.003454426,0.002892528,0.001521207,0.12581],"category_scores_gemma":[0.009422336,0.0006644207,0.00158714,0.006201448,0.000320163,0.002504773,0.001769321,0.001754093,0.2380911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001662918,"about_ca_system_score_gemma":0.002528021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01652452,"about_ca_topic_score_gemma":0.02316351,"domain_scores_codex":[0.9973912,0.0003610248,0.000301924,0.0008515766,0.0008655155,0.0002288378],"domain_scores_gemma":[0.9962042,0.000715612,0.0003314346,0.0009693733,0.001642308,0.000137055],"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":[0.0001200018,0.00002164257,0.001117468,0.0006787898,0.00004894922,0.00001847741,0.00001431925,0.000395202,0.0002151563,0.0008846235,0.977389,0.01909631],"study_design_scores_gemma":[0.00007364707,0.00001362121,0.002108816,0.0002188368,0.0000363568,0.00005614525,0.00003623693,0.0004672174,0.0007683882,0.002349782,0.9938437,0.00002729801],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001751113,0.0002777448,0.0009953516,0.000129823,0.00008712631,0.00004385701,0.9907794,0.002060271,0.00545137],"genre_scores_gemma":[0.0008058767,0.0003277559,0.002454816,0.0001966216,0.00002589314,0.0001546781,0.9920304,0.0003496488,0.003654255],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.12581,"threshold_uncertainty_score":0.4208765,"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."}}