{"id":"W4403071917","doi":"10.1007/978-3-031-72384-1_2","title":"A Clinical-Oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-Quality Medical Images","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Quality (philosophy); Artificial intelligence; Contrastive analysis; Natural language processing; Linguistics","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":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.005765689,0.0006137882,0.001377035,0.0008928025,0.0001442248,0.0001348676,0.0006818195,0.000593441,0.00008363706],"category_scores_gemma":[0.01750149,0.0005295483,0.0004693196,0.0006164099,0.001238247,0.0001333778,0.0007028522,0.002400587,0.00002665685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006664702,"about_ca_system_score_gemma":0.00204516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001517785,"about_ca_topic_score_gemma":0.0002802046,"domain_scores_codex":[0.9940408,0.0002173336,0.001359521,0.002219287,0.001408117,0.0007549424],"domain_scores_gemma":[0.9815078,0.01627326,0.0003381018,0.0007022156,0.0004603062,0.0007183319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004019675,0.0007214976,0.01904927,0.00155047,0.0001182937,0.001337321,0.0009350671,0.005655298,0.00002590557,0.0008684656,0.0003127083,0.9690238],"study_design_scores_gemma":[0.005565065,0.0007254157,0.0415924,0.01995737,0.0003611695,0.0000297015,0.000002796553,0.9000115,0.0003766999,0.01517173,0.01488175,0.001324332],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00041971,0.001309421,0.9743686,0.02033322,0.001749195,0.001502814,0.0001065991,0.0001693645,0.00004106058],"genre_scores_gemma":[0.1104864,0.0009736168,0.8257634,0.05750708,0.002770509,0.0006408033,0.0001617068,0.0002845162,0.001411945],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9676994,"threshold_uncertainty_score":0.9999009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08241337606324936,"score_gpt":0.4430579512729389,"score_spread":0.3606445752096895,"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."}}