{"id":"W4286494955","doi":"10.1038/s41597-022-01552-7","title":"The Multilingual Picture Database","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Categorization, perception, and language","field":"Psychology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre for Research on Brain Language and Music","funders":"Department of Education and Training; Saint Petersburg State University; Israel Science Foundation; Academy of Finland; Narodowe Centrum Nauki; National Research Foundation of Korea; Comunidad de Madrid","keywords":"Multilingualism; Computer science; Psycholinguistics; Variety (cybernetics); Field (mathematics); Value (mathematics); Linguistics; Natural language processing; Artificial intelligence; Psychology; Mathematics; Cognition","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":[0.001303102,0.001862387,0.00132148,0.005034498,0.001248197,0.002527362,0.00417363,0.002257033,0.03571274],"category_scores_gemma":[0.007008065,0.0005948052,0.001178661,0.006508165,0.0006190455,0.003892282,0.004170771,0.002235455,0.04547102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001543795,"about_ca_system_score_gemma":0.00251896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01805936,"about_ca_topic_score_gemma":0.0294046,"domain_scores_codex":[0.9980515,0.0003194593,0.000311158,0.0005916872,0.000535833,0.0001903101],"domain_scores_gemma":[0.9974274,0.0003752051,0.000206085,0.0009184047,0.0007145139,0.000358374],"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":[0.0004835436,0.000200083,0.004206754,0.001945137,0.0001287318,0.0003452586,0.0002967748,0.0007643849,0.001941499,0.003070047,0.9545405,0.0320773],"study_design_scores_gemma":[0.0002897153,0.00008671256,0.01393785,0.0003071291,0.00007147203,0.0005368543,0.0006864253,0.00299593,0.002543292,0.002943095,0.9754938,0.0001076591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00487973,0.0006417665,0.001607752,0.0002720972,0.00008986301,0.0001979702,0.9835932,0.003703338,0.005014272],"genre_scores_gemma":[0.003598695,0.0001189339,0.002275194,0.00006399993,0.00001019337,0.0002149532,0.9927282,0.000176636,0.0008131388],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03571274,"threshold_uncertainty_score":0.1194711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06283960389950143,"score_gpt":0.3644330016659291,"score_spread":0.3015933977664276,"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."}}