{"id":"W6930928281","doi":"10.5281/zenodo.15779015","title":"QIRT Benzene Ring Hardware Benchmark Dataset (IBM Sherbrooke, July 2025)","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Firmware; Software; Quantum computer; Raw data; Quantum; Debugging; IBM","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009231367,0.002377322,0.001141351,0.001681888,0.0009175958,0.001593292,0.004068128,0.002345482,0.03160217],"category_scores_gemma":[0.004138336,0.0005324096,0.001165706,0.00370536,0.0005058325,0.001064267,0.001515959,0.001581115,0.03928284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00207615,"about_ca_system_score_gemma":0.002295826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02577645,"about_ca_topic_score_gemma":0.04511249,"domain_scores_codex":[0.9989792,0.0001622983,0.0000737616,0.0002570061,0.0003854452,0.0001422991],"domain_scores_gemma":[0.9987729,0.0002919731,0.00009895835,0.0003840807,0.0003507373,0.0001012815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001307056,0.00005657202,0.000879317,0.0006220855,0.00004293233,0.00004470374,0.0000149258,0.002958374,0.0004348995,0.001393261,0.9892719,0.004150399],"study_design_scores_gemma":[0.0006424899,0.0001258676,0.005585647,0.0002680479,0.0000635552,0.0001504413,0.00007511809,0.0110861,0.003060583,0.006547841,0.9723322,0.00006209059],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001236224,0.0002689111,0.0005054742,0.0001716429,0.00004324723,0.00002893621,0.9936326,0.002070596,0.002042506],"genre_scores_gemma":[0.001649008,0.00006946763,0.0007690559,0.0000638786,0.000005656565,0.00006260807,0.9966727,0.0001113431,0.0005962686],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03160217,"threshold_uncertainty_score":0.1057198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0385446373980602,"score_gpt":0.2935553572911184,"score_spread":0.2550107198930582,"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."}}