{"id":"W4224078729","doi":"10.1371/journal.pone.0266359","title":"Standardizing norms for 180 coloured Snodgrass and Vanderwart pictures in Kannada language","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Felix Scholarship","keywords":"Kannada; Computer science; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003112498,0.0001031765,0.000217832,0.0001040839,0.0001535831,0.00002311844,0.00009120571,0.0000499335,0.001171642],"category_scores_gemma":[0.00005767102,0.0000971952,0.00003787086,0.0001264195,0.00002525217,0.00004169686,0.00004991813,0.0001850719,0.000009155694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004796267,"about_ca_system_score_gemma":0.00002148584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000280435,"about_ca_topic_score_gemma":0.000713366,"domain_scores_codex":[0.9990159,0.0001043941,0.0001591586,0.0002474844,0.0002237539,0.0002492835],"domain_scores_gemma":[0.9995926,0.0001102729,0.00005738532,0.0001605989,0.00003193496,0.00004723355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.01078046,0.01877887,0.09602166,0.001746431,0.00565804,0.002004508,0.3686525,0.00006195898,0.3155061,0.0188037,0.05258126,0.1094045],"study_design_scores_gemma":[0.07346439,0.01016747,0.2381369,0.0006795857,0.003562723,0.0003044744,0.4172796,0.001458354,0.1290375,0.05189086,0.06829146,0.005726713],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918647,0.001320031,0.0002040719,0.0002654379,0.000143534,0.0005241584,0.0001699338,0.00005486372,0.005453297],"genre_scores_gemma":[0.9961563,0.00001026611,0.0004397933,0.0006775846,0.0001100368,0.0004018694,0.00009573771,0.00002353738,0.002084812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1864686,"threshold_uncertainty_score":0.9997414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246751169223586,"score_gpt":0.2789279377331007,"score_spread":0.2464604260408648,"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."}}