{"id":"W2931336337","doi":"10.31438/trf.hh2016.59","title":"A HIGHLY SENSITIVE SMALL-FOOTPRINT VOX-BASED MICRO-PIRANI GAUGE FOR IN-SITU MONITORING OF VACUUM WAFER-LEVEL PACKAGED BOLOMETERS","year":2016,"lang":"en","type":"article","venue":"2016 Solid-State, Actuators, and Microsystems Workshop Technical Digest","topic":"Transition Metal Oxide Nanomaterials","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalsa Corporation; Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Wafer; Bolometer; Materials science; Wafer-level packaging; Footprint; Optoelectronics; Spark plug; Leak; Temperature measurement; Torr; Electrical engineering; Mechanical engineering; Engineering; Physics; Detector","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006924575,0.0005562055,0.00036951,0.0003746197,0.0001611678,0.0003341117,0.001095047,0.0003619714,0.0007887817],"category_scores_gemma":[0.00106562,0.0003605909,0.0001774576,0.0002062228,0.0003817633,0.0006175001,0.0003879712,0.000515346,0.0002934514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002859432,"about_ca_system_score_gemma":0.0002202778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002745837,"about_ca_topic_score_gemma":0.000767077,"domain_scores_codex":[0.9993948,0.00009452661,0.00002610318,0.0001111171,0.0003168899,0.00005659038],"domain_scores_gemma":[0.9992059,0.000212457,0.0002278425,0.000149415,0.000148629,0.00005571843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003881941,0.00002752815,0.001226191,0.0001215665,0.000009175094,0.00009469743,0.0000663444,0.0004332334,0.9860188,0.0002771876,0.0002582897,0.01142818],"study_design_scores_gemma":[0.000008893068,0.0003634301,0.003084151,0.000007390635,0.00001293302,0.0002902426,0.00003415749,0.003375224,0.9892674,0.00005957434,0.003471648,0.00002496398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7879688,0.002116943,0.2024034,0.00034861,0.000295661,0.0004156822,0.0006484216,0.002251601,0.003550931],"genre_scores_gemma":[0.8261458,0.0004814187,0.1708558,0.00009541617,0.0000470764,0.0001703701,0.0001670319,0.0001001191,0.001936841],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001095047,"threshold_uncertainty_score":0.003662109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02778525885514271,"score_gpt":0.2677423647492602,"score_spread":0.2399571058941175,"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."}}