{"id":"W4413981801","doi":"10.3390/biomedinformatics5030051","title":"Quantum-Enhanced Dual-Backbone Architecture for Accurate Gastrointestinal Disease Detection Using Endoscopic Imaging","year":2025,"lang":"en","type":"article","venue":"BioMedInformatics","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Moncton","keywords":"Dual (grammatical number); Architecture; Computer science; Quantum; Medicine; Artificial intelligence; Computer vision; Physics; Philosophy; History; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004323639,0.0002624957,0.0002769695,0.0002374919,0.0002205615,0.0003446681,0.0008843758,0.0005247206,0.001682904],"category_scores_gemma":[0.0008848386,0.0001472976,0.0002281231,0.000213302,0.0004743268,0.0008839626,0.0005876018,0.0004627582,0.0003004158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006993799,"about_ca_system_score_gemma":0.000682144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002108757,"about_ca_topic_score_gemma":0.003206506,"domain_scores_codex":[0.9999102,0.0000218781,0.000003208359,0.00002311149,0.00002657059,0.00001500275],"domain_scores_gemma":[0.9998259,0.00005946043,0.00002315479,0.00002695191,0.00004801317,0.00001651322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003332897,0.000253737,0.004794376,0.000198671,0.0001042474,0.0001860225,0.0001050053,0.6188113,0.06471022,0.02759766,0.005174951,0.2777305],"study_design_scores_gemma":[0.000004528057,0.00002968586,0.0001879275,0.00000244859,0.000006767954,0.00001737859,0.000003277245,0.9939986,0.002619237,0.00269818,0.000428955,0.000003048035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1716531,0.0007963313,0.8200008,0.0008210418,0.00006835235,0.00005366823,0.0001410385,0.001202957,0.005262733],"genre_scores_gemma":[0.9103165,0.0002250259,0.08711502,0.0001928434,0.00002044577,0.00004062662,0.0001257566,0.00002852693,0.001935218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002108757,"threshold_uncertainty_score":0.005629897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201575293797259,"score_gpt":0.265816544482688,"score_spread":0.2538007915447154,"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."}}