{"id":"W4400529953","doi":"10.1016/j.cell.2024.05.020","title":"Advancing accessible science for low-vision and diverse-needs communities","year":2024,"lang":"en","type":"article","venue":"Cell","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"Lions Eye Institute; Australian Research Council Centre of Excellence in Advanced Molecular Imaging; Monash University; Australian Research Council; University of New South Wales; University of Cambridge; European Molecular Biology Laboratory","keywords":"Biology; Data science; Computational biology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0003410281,0.00007535363,0.0001121142,0.0002708454,0.0002254401,0.0001378006,0.0001065653,0.00002816317,0.0000448725],"category_scores_gemma":[0.0000610795,0.00006271381,0.00003062477,0.0003611259,0.0002174212,0.0002550106,0.0001154167,0.0001045089,0.00001731631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009703952,"about_ca_system_score_gemma":0.0002230321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009953868,"about_ca_topic_score_gemma":0.00001418426,"domain_scores_codex":[0.9994339,0.000008620986,0.00008835612,0.0001300626,0.0001500068,0.0001890895],"domain_scores_gemma":[0.9992043,0.0004307114,0.00001577753,0.0001986804,0.00006574977,0.00008475708],"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":[0.0002509299,0.0007688494,0.01841813,0.01698139,0.00005737276,0.0001303972,0.04359255,0.0003596063,0.6294047,0.00154583,0.192351,0.09613921],"study_design_scores_gemma":[0.001892643,0.0007338606,0.004840527,0.003931182,0.0002194093,0.00002122834,0.009798952,0.0441342,0.2703312,0.0005903754,0.6631224,0.0003840784],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989628,0.001908095,0.0007307644,0.004969705,0.0004822639,0.0002751542,0.00000713985,0.0001422136,0.001856633],"genre_scores_gemma":[0.9949762,0.0002347116,0.001043016,0.002686141,0.00008042771,0.0000123508,0.000005124873,0.00001461197,0.0009474598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4707713,"threshold_uncertainty_score":0.2557395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03004372790384717,"score_gpt":0.3539934901512441,"score_spread":0.3239497622473969,"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."}}