{"id":"W6968757546","doi":"10.5281/zenodo.16881092","title":"MIR2 raw data","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Raw material; Raw data; Product (mathematics); Production (economics); Data collection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001482188,0.005140599,0.002185128,0.004593341,0.00154691,0.003201999,0.003420441,0.003317868,0.1295647],"category_scores_gemma":[0.006418629,0.001150736,0.002617016,0.005710776,0.0007769231,0.001568384,0.002523365,0.002638601,0.2758802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001126624,"about_ca_system_score_gemma":0.002580815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01554016,"about_ca_topic_score_gemma":0.02685676,"domain_scores_codex":[0.9977381,0.0004379459,0.0001534114,0.0006969556,0.0006279175,0.0003456474],"domain_scores_gemma":[0.9976805,0.0005916249,0.0001330534,0.0007521014,0.0005790606,0.0002634847],"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":[0.0001181986,0.0000345467,0.0002410894,0.0004165242,0.00003407496,0.000022161,0.00001651713,0.000475027,0.0004280485,0.0003105781,0.9953319,0.002571325],"study_design_scores_gemma":[0.0003750971,0.00006217502,0.002005372,0.0002140928,0.0000817499,0.0001058346,0.00007929913,0.001736662,0.001900525,0.002918528,0.9904494,0.00007131264],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002710199,0.0001616237,0.0003692386,0.00007989853,0.00009052412,0.00002559604,0.9942588,0.003051724,0.001691716],"genre_scores_gemma":[0.0003441597,0.00004736917,0.00068927,0.00006372656,0.00001148859,0.00007298737,0.9971799,0.0004119644,0.001179221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1295647,"threshold_uncertainty_score":0.4334372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0710614958483857,"score_gpt":0.3012040203512959,"score_spread":0.2301425245029102,"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."}}