{"id":"W7106276781","doi":"10.5281/zenodo.17656412","title":"Sub-second and Dynamic Computed Tomography Development at the Canadian Light Source","year":2021,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada); University of Saskatchewan","funders":"","keywords":"Tomographic reconstruction; Data acquisition; Sample (material); Tomography; Process (computing); Dynamic imaging; Computed tomographic; Computed tomography; Medical imaging","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004314604,0.0002841076,0.0002108585,0.0002868756,0.006694139,0.001309482,0.0006325501,0.0001026949,0.01127001],"category_scores_gemma":[0.0001246115,0.0002985868,0.00006184953,0.0009758456,0.0002191581,0.000240592,0.001258174,0.0005440143,0.002710887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006770469,"about_ca_system_score_gemma":0.000029017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001408812,"about_ca_topic_score_gemma":0.001849633,"domain_scores_codex":[0.9977716,0.0002479669,0.0003581954,0.0005446496,0.0003299156,0.0007476246],"domain_scores_gemma":[0.9984317,0.00003452562,0.00007437252,0.0005105357,0.0004550806,0.0004937282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007330068,0.0001730911,0.0000832663,0.0008446617,0.0008104908,0.0003671505,0.02211062,0.009381876,0.03727045,0.001763193,0.07881992,0.8483019],"study_design_scores_gemma":[0.0004009853,0.00003110432,0.002723053,0.00008507882,0.00002387853,0.0003495031,0.0005626483,0.005637427,0.006009315,0.00004049204,0.9837769,0.0003595671],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5942852,0.02851585,0.080351,0.01063558,0.0017023,0.002675083,0.001001927,0.003313573,0.2775195],"genre_scores_gemma":[0.9927338,0.0002810495,0.0006093945,0.0003106613,0.00008567319,6.387533e-8,0.001095733,0.001737142,0.003146517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.904957,"threshold_uncertainty_score":0.9999467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013196171065117,"score_gpt":0.1928239102637527,"score_spread":0.1826919485531015,"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."}}