{"id":"W2603321276","doi":"","title":"Belief Function Based Algorithm for Material Detection and Tracking in Construction","year":2010,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"RFID technology advancements","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Focus (optics); Tracking (education); Track (disk drive); Computer science; Identification (biology); Function (biology); Dislocation; Algorithm; Materials science; Physics; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00144778,0.0002440736,0.0002450349,0.0003142221,0.0001469806,0.0001399279,0.0002536462,0.0005493162,0.00003483926],"category_scores_gemma":[0.0002192829,0.0003093407,0.00006077618,0.0001713026,0.0001409159,0.0001487374,0.0001652655,0.0006640211,0.000002676524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211804,"about_ca_system_score_gemma":0.00003681461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001387116,"about_ca_topic_score_gemma":0.001180241,"domain_scores_codex":[0.9984094,0.0003924064,0.0003731813,0.0004490737,0.0001329026,0.000243053],"domain_scores_gemma":[0.9984253,0.0002605679,0.0001689412,0.0006695365,0.0004228743,0.00005275384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001282018,0.00006626765,0.000280991,0.0001663064,0.00002982576,7.177724e-7,0.0001998629,0.0004700372,0.05800325,0.001146825,0.00001130243,0.9396118],"study_design_scores_gemma":[0.0009122905,7.734963e-7,0.002421487,0.0005180415,0.00003848138,0.000007819005,0.00002939371,0.5023819,0.4850879,0.005561751,0.002689098,0.0003510646],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2078261,0.0001950419,0.7889614,0.0002451784,0.001090406,0.0005452388,0.00006643163,0.0004761159,0.0005940733],"genre_scores_gemma":[0.7543998,0.0001617796,0.2446956,0.00001214804,0.00003485583,0.0002778147,0.0002972439,0.00005546947,0.00006531305],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9392607,"threshold_uncertainty_score":0.9999359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007278875050138171,"score_gpt":0.2079605585013355,"score_spread":0.2006816834511973,"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."}}