{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001748344,0.004576636,0.002003456,0.00387527,0.0006775412,0.002203814,0.002199407,0.002975355,0.009449688],"category_scores_gemma":[0.004999864,0.0005557924,0.002284873,0.002864392,0.00076452,0.001191643,0.001502642,0.001147308,0.01137645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001413353,"about_ca_system_score_gemma":0.001360877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02409056,"about_ca_topic_score_gemma":0.04994785,"domain_scores_codex":[0.9982114,0.0002260001,0.0001598999,0.0006144439,0.0005521098,0.0002361413],"domain_scores_gemma":[0.9983243,0.0004182734,0.0001128745,0.0004907751,0.0005300161,0.0001237482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002271655,0.0008614592,0.008758601,0.005397297,0.001043411,0.0004651822,0.0001074241,0.01844126,0.01208735,0.001026239,0.8025783,0.1469617],"study_design_scores_gemma":[0.002016345,0.001165958,0.06171098,0.00185128,0.001457083,0.005008509,0.0005875016,0.1643203,0.066428,0.008094138,0.6868824,0.0004775416],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04506936,0.005714975,0.01579747,0.0006310322,0.0007026785,0.0005862283,0.8990898,0.0233543,0.009054149],"genre_scores_gemma":[0.02380948,0.0006901264,0.01544013,0.00017426,0.00004562256,0.0002148657,0.9554636,0.000694083,0.003467815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02409056,"threshold_uncertainty_score":0.04790068,"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."}}