{"id":"W6958385062","doi":"10.6084/m9.figshare.19328939.v5","title":"MultiPic: Multilingual Picture Database","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mandarin Chinese; Malay; Set (abstract data type); Data set; Government (linguistics); Estonian","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001170646,0.0008670862,0.0006320114,0.0004195817,0.0003618276,0.000151197,0.002287728,0.0005329663,0.993488],"category_scores_gemma":[0.007380094,0.0008995243,0.0002932136,0.000519374,0.00001314842,0.0002117327,0.002881676,0.00269547,0.2014062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003476427,"about_ca_system_score_gemma":0.000472184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001434546,"about_ca_topic_score_gemma":0.0004581454,"domain_scores_codex":[0.9959558,0.0002516446,0.0004937273,0.001278377,0.001226507,0.0007939403],"domain_scores_gemma":[0.9958497,0.0002579879,0.0005703215,0.002827073,0.000175524,0.0003193897],"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":[0.00003949053,0.0001744123,2.331333e-7,0.001046953,0.0000821645,0.00111183,0.00003438522,0.0000370331,0.00001450466,2.559395e-8,0.9973268,0.0001321811],"study_design_scores_gemma":[0.0006673207,0.00004062378,0.00001056349,0.001412646,0.00008407242,0.00005729201,0.00004024496,0.00003241726,0.00006705189,3.770585e-7,0.9966207,0.0009666545],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001051922,0.001144944,4.428809e-9,0.000005270741,0.0003572938,0.0009055065,0.9971136,0.0004091632,0.00006315368],"genre_scores_gemma":[0.000001633011,0.000005053723,0.00003129771,0.0004386666,0.0009164397,0.001143296,0.9967268,0.000279402,0.0004574776],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7920818,"threshold_uncertainty_score":0.9996054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07766491267446812,"score_gpt":0.3423546073327636,"score_spread":0.2646896946582955,"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."}}