{"id":"W1552473270","doi":"10.1109/nssmic.2005.1596913","title":"The Architecture of LabTEP, a Small Animal APD-Based Digital PET Scanner","year":2006,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Xilinx","keywords":"Scanner; Computer science; Architecture; Artificial intelligence; Art","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":[0.0003066945,0.0003773344,0.0004443704,0.0005009345,0.000302603,0.0008986506,0.002195139,0.0007627056,0.0105782],"category_scores_gemma":[0.0005090488,0.0003910023,0.0002230664,0.000383161,0.0003204012,0.0007950603,0.0007199281,0.0005453239,0.005403675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005417053,"about_ca_system_score_gemma":0.001028494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009832119,"about_ca_topic_score_gemma":0.001147504,"domain_scores_codex":[0.9997755,0.0000294332,0.00001175154,0.00006812649,0.0000949053,0.00002032033],"domain_scores_gemma":[0.9997671,0.00003944661,0.00001718408,0.00005649163,0.00007170104,0.00004799167],"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":[0.001331656,0.0002066614,0.003294544,0.0009815779,0.0001143796,0.001281071,0.0002474938,0.01487518,0.499123,0.01393311,0.03798717,0.4266241],"study_design_scores_gemma":[0.000419767,0.002283555,0.008529957,0.0001741856,0.0002821708,0.009112736,0.0001255261,0.2456133,0.293282,0.007774394,0.4321308,0.00027166],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03509358,0.0008384053,0.9126523,0.001087924,0.0003115835,0.001126909,0.001410366,0.02219302,0.02528595],"genre_scores_gemma":[0.2282666,0.0007297124,0.7323559,0.00172903,0.0001338779,0.001655434,0.002530103,0.0005239204,0.0320754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0105782,"threshold_uncertainty_score":0.03538764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009975346665093988,"score_gpt":0.2556146178397865,"score_spread":0.2456392711746925,"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."}}