{"id":"W6968393378","doi":"10.5281/zenodo.15285967","title":"SPCG Computational Artifact for SC25","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Artifact (error); Feature (linguistics); Noise (video); Set (abstract data type)","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001130872,0.0002465699,0.0002875393,0.0003939347,0.001421065,0.001274032,0.001633795,0.0001470307,0.1523302],"category_scores_gemma":[0.001226355,0.0002531867,0.00007380123,0.0003289927,0.0002692009,0.0001181613,0.001039341,0.0001999525,0.0224524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185317,"about_ca_system_score_gemma":0.00001930062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005579479,"about_ca_topic_score_gemma":7.21944e-7,"domain_scores_codex":[0.9976127,0.0003723053,0.0003215128,0.0007286597,0.000504787,0.0004600714],"domain_scores_gemma":[0.9986059,0.00007086196,0.0002780508,0.0005208091,0.0003889573,0.0001354286],"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":[0.00003510906,0.00005836209,5.181947e-7,0.0002280038,0.00001569484,0.000003302102,0.00009389912,0.00109587,0.008818895,0.007034358,0.9746508,0.007965175],"study_design_scores_gemma":[0.0003279929,0.0001035324,0.00004023618,0.0001316798,0.00001698752,0.00001787205,0.0000206202,0.001756026,0.0005968965,0.0009282782,0.9958038,0.0002560984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002278816,0.00008922094,0.1035163,0.0007180573,0.0008499732,0.001101133,0.00198518,0.002414453,0.8890978],"genre_scores_gemma":[0.009908981,0.00006555225,0.05225308,0.000864793,0.001506289,7.913782e-7,0.009122645,0.01405162,0.9122263],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1298778,"threshold_uncertainty_score":0.999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387416727287491,"score_gpt":0.2721165814351881,"score_spread":0.2482424141623132,"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."}}