{"id":"W2573602261","doi":"10.1109/icsens.2016.7808584","title":"A vector light detector for proximity sensing applications","year":2016,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Photodiode; Computer science; Detector; Pixel; Photodetector; Pyramid (geometry); Automation; Electronic engineering; Artificial intelligence; Optics; Optoelectronics; Materials science; Engineering; Physics; Mechanical engineering; Telecommunications","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":[0.0003473806,0.0005023767,0.000391215,0.0005430997,0.0003318134,0.001034165,0.0008833635,0.0008558113,0.002957639],"category_scores_gemma":[0.0003482545,0.0003119757,0.0002696524,0.0004198308,0.0003295713,0.0009846129,0.0006252725,0.0006245313,0.001704584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004884215,"about_ca_system_score_gemma":0.000508439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003012797,"about_ca_topic_score_gemma":0.0006014085,"domain_scores_codex":[0.999479,0.00005594124,0.00002173638,0.0001157977,0.0002964712,0.00003115526],"domain_scores_gemma":[0.9997378,0.00004941622,0.00004450479,0.00003217265,0.0001012357,0.00003492865],"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":[0.0000875236,0.00005511502,0.0006593281,0.0002220673,0.00001897667,0.0001285324,0.00004274099,0.0007531049,0.9097598,0.007281739,0.001822289,0.07916892],"study_design_scores_gemma":[0.00002813213,0.0006621431,0.001389594,0.00002920434,0.00004347087,0.001455046,0.00004753597,0.03079122,0.8952456,0.001361184,0.06888393,0.00006290806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07143191,0.004329859,0.9026975,0.0006988119,0.0007000102,0.0003332829,0.0003798251,0.003057599,0.01637123],"genre_scores_gemma":[0.4227777,0.002079928,0.5558072,0.00067167,0.0001683795,0.0002185762,0.0003942806,0.0001058149,0.0177764],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002957639,"threshold_uncertainty_score":0.009894311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007380335783191618,"score_gpt":0.2031009721560344,"score_spread":0.1957206363728428,"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."}}