{"id":"W2188479190","doi":"10.3758/s13428-015-0679-8","title":"Thematic relatedness production norms for 100 object concepts","year":2015,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Thematic map; Locative case; Attributive; Computer science; Object (grammar); Similarity (geometry); Cognition; Cognitive science; Psychology; Cognitive psychology; Linguistics; Natural language processing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01362339,0.0004465528,0.0004157083,0.001953498,0.0004460073,0.00205022,0.0007758826,0.0009610146,0.006894723],"category_scores_gemma":[0.1328257,0.0003475871,0.0004848875,0.000609415,0.001231581,0.001813832,0.001785857,0.00104662,0.001028944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007462473,"about_ca_system_score_gemma":0.0003716135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001018087,"about_ca_topic_score_gemma":0.001189069,"domain_scores_codex":[0.991275,0.002933906,0.000872155,0.001362296,0.003283802,0.0002728504],"domain_scores_gemma":[0.8658892,0.1065552,0.006183805,0.007088768,0.01311757,0.001165521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.009149589,0.001761334,0.3094105,0.001537106,0.0008256841,0.001210212,0.04429682,0.01134142,0.1852141,0.09027265,0.007945807,0.3370349],"study_design_scores_gemma":[0.0004911001,0.002278474,0.8011915,0.0003886989,0.0004313775,0.00351408,0.00657439,0.04159157,0.05213133,0.07554261,0.01555439,0.0003104803],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9332553,0.0002751982,0.02408048,0.0001347831,0.00009338827,0.0003522352,0.001029919,0.0003500085,0.04042874],"genre_scores_gemma":[0.9784316,0.00008810978,0.01676977,0.00004621924,0.00003793742,0.0006067273,0.001240829,0.00031977,0.002459062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01362339,"threshold_uncertainty_score":0.07204819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6433840902575432,"score_gpt":0.6503699384502034,"score_spread":0.006985848192660238,"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."}}