{"id":"W7086987655","doi":"10.5281/zenodo.17300994","title":"SwanHubX/SwanLab: v0.6.11","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xanadu Quantum Technologies (Canada)","funders":"","keywords":"Interrupt; Chart; Login; Check-in; Dependency (UML); Constraint (computer-aided design)","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":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004112137,0.0002569822,0.0003313768,0.001441216,0.00168154,0.004047878,0.00508045,0.0001421819,0.1541408],"category_scores_gemma":[0.005684054,0.0002303948,0.000123966,0.002039701,0.0002392055,0.0001443837,0.005766563,0.0002959321,0.08545725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001065551,"about_ca_system_score_gemma":0.0000125091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000100369,"about_ca_topic_score_gemma":0.000004270285,"domain_scores_codex":[0.9952004,0.0006082766,0.0005392028,0.001399916,0.00177774,0.0004744931],"domain_scores_gemma":[0.9965503,0.00012175,0.0003397758,0.002066009,0.0007155038,0.0002067098],"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":[0.000006072602,0.0000506401,8.603281e-7,0.00002092542,0.00002621266,0.00001051274,0.0001000706,0.00001116764,0.0000159635,0.006498277,0.81574,0.1775192],"study_design_scores_gemma":[0.0002477863,0.00004001471,0.00006323063,0.00008689955,0.0000178562,0.000008905681,0.0002069605,0.0002700112,0.000008873562,0.0009547215,0.997865,0.0002297841],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0000135354,0.0001741899,0.02029135,0.001151515,0.0009154514,0.0004323505,0.001037316,0.001566665,0.9744176],"genre_scores_gemma":[0.001392752,0.00004090374,0.0006566205,0.0002497431,0.0003401664,2.410696e-8,0.001636183,0.002861805,0.9928218],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1821249,"threshold_uncertainty_score":0.9996181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126139502545992,"score_gpt":0.3397988456794887,"score_spread":0.2271848954248895,"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."}}