{"id":"W2077377457","doi":"10.1109/dtis.2008.4540240","title":"High precision time-to-amplitude converter for diffuse optical tomography applications","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Integrator; Scanner; Diffuse optical imaging; Digital micromirror device; Time-to-digital converter; CMOS; Analog-to-digital converter; Optical tomography; Dead time; Photon counting; Image resolution; Computer science; Amplitude; Physics; Optics; Electronic engineering; Optoelectronics; Electronic circuit; Detector; Tomography; Voltage; Engineering; Telecommunications; Bandwidth (computing)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002630635,0.0001256462,0.0001676066,0.0000589822,0.0001419098,0.00001897949,0.0001769923,0.00004832436,0.000239762],"category_scores_gemma":[0.00001525346,0.0001024984,0.00009497274,0.000177367,0.0001152122,0.00006099635,0.00009393161,0.00008028557,0.0005304826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001223613,"about_ca_system_score_gemma":0.0000091045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005967289,"about_ca_topic_score_gemma":1.849313e-7,"domain_scores_codex":[0.9992009,0.000004233615,0.0001653367,0.0002827021,0.00009678921,0.0002500351],"domain_scores_gemma":[0.9992313,0.0002161794,0.0000256137,0.0003582798,0.0000748371,0.00009372272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008393937,0.001106258,0.003884656,0.000008087568,0.0001285719,0.000001416387,0.00005558248,0.0001632662,0.01634392,0.6621506,0.01447391,0.3015997],"study_design_scores_gemma":[0.00466227,0.0007395832,0.01327669,0.00004562486,0.0001251615,0.00000753807,0.0001440583,0.005567592,0.1505139,0.5970139,0.2260838,0.001819861],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05280633,0.000003720395,0.9420733,0.0005985459,0.00002583582,0.0006955208,0.0000233543,0.0002904522,0.003482884],"genre_scores_gemma":[0.6725709,3.204987e-7,0.3257764,0.0001102476,0.00006990721,0.0002151929,0.00002419211,0.00001568339,0.001217133],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6197646,"threshold_uncertainty_score":0.6818458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109572730535678,"score_gpt":0.2450325558664797,"score_spread":0.233936828561123,"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."}}