{"id":"W6894109690","doi":"10.5291/ill-data.test-3078","title":"Evaluation of image quality using a specific test object","year":2020,"lang":"en","type":"dataset","venue":"Institut Laue-Langevin","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Essays on Canadian Writing","funders":"","keywords":"Object (grammar); Image quality; Image (mathematics); Quality (philosophy); Image processing; Pattern recognition (psychology); Test (biology)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001354565,0.0004235076,0.0005692147,0.0002929899,0.0002065528,0.0001629448,0.0006342897,0.0002175642,0.0007855569],"category_scores_gemma":[0.006432249,0.0004285902,0.0001660363,0.0006156888,0.0001831378,0.0003478465,0.0001906715,0.0004966463,0.001054179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446188,"about_ca_system_score_gemma":0.0006750468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000559761,"about_ca_topic_score_gemma":0.00009303265,"domain_scores_codex":[0.9944623,0.001215329,0.0009506448,0.0009244619,0.002153059,0.000294262],"domain_scores_gemma":[0.997364,0.0003918256,0.0008299083,0.0009165473,0.0003471163,0.0001506474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001449381,0.00008578064,5.964451e-7,0.0001003614,0.000004242247,0.00003664558,0.00002093552,0.0001064871,0.5499181,0.0001816591,0.4492798,0.0002508909],"study_design_scores_gemma":[0.0006499363,0.00008170187,0.00001859457,0.00008103446,0.0001504238,0.00003113746,0.0000079765,0.0009990546,0.4317141,0.0001077005,0.565795,0.0003633187],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006580161,0.00007330456,0.0002695259,0.0001379028,0.001565561,0.001229334,0.9889675,0.0001294028,0.001047331],"genre_scores_gemma":[0.01612057,0.0009951366,0.001172413,0.003012675,0.001911358,0.0001593993,0.9763023,0.000139614,0.0001865009],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.118204,"threshold_uncertainty_score":0.9998166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2469114585138895,"score_gpt":0.382887869547619,"score_spread":0.1359764110337295,"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."}}