{"id":"W2951620778","doi":"10.48550/arxiv.0809.3910","title":"A globally accelerated numerical method for optical tomography with continuous wave source","year":2008,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Army Research Laboratory; Army Research Office; National Institutes of Health","keywords":"Tomography; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006075656,0.0007011948,0.0005088816,0.0005297018,0.0003181591,0.0005446224,0.0008250417,0.0008402126,0.001920614],"category_scores_gemma":[0.001584348,0.0002636271,0.000526847,0.0004141937,0.0008528149,0.0008314498,0.001178348,0.001186105,0.0006227873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004789456,"about_ca_system_score_gemma":0.0007606561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079918,"about_ca_topic_score_gemma":0.001060597,"domain_scores_codex":[0.9997025,0.0000855355,0.000009721986,0.00003452672,0.0001535518,0.00001414129],"domain_scores_gemma":[0.99959,0.000134228,0.00004812202,0.00005746449,0.0001413072,0.00002889584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001516486,0.00005330297,0.0008405314,0.0002701214,0.00005144079,0.0002405594,0.0002487443,0.4818977,0.05534011,0.2537929,0.004531079,0.2025818],"study_design_scores_gemma":[0.00001346015,0.00003886172,0.00008627566,0.00001072892,0.000006334129,0.00009113439,0.000007345434,0.9781556,0.002802433,0.01209744,0.006675144,0.00001515727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001992124,0.00009602946,0.9966372,0.00006480913,0.00005449196,0.00001193206,0.00001004159,0.00009774992,0.001035486],"genre_scores_gemma":[0.1070899,0.0003792147,0.8827836,0.0001154821,0.0001028645,0.0001916725,0.00009160343,0.0002906615,0.008955042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001920614,"threshold_uncertainty_score":0.006425083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1823866134557689,"score_gpt":0.2759387597774305,"score_spread":0.09355214632166156,"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."}}