{"id":"W4394169281","doi":"10.6084/m9.figshare.24955719","title":"Identification and Description of Emotions by Current Large Language Models - Dataset","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Current (fluid); Computer science; Natural language processing; Psychology; Cognitive psychology; Cognitive science; Geology; Biology; Oceanography; Ecology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00008734145,0.0001470143,0.0001497201,0.0001308545,0.00004886391,0.0002346881,0.0006908987,0.00011098,0.002810714],"category_scores_gemma":[0.00009441742,0.0001491204,0.00003598244,0.0001517116,0.000003731408,0.0005220993,0.0006081536,0.0002466799,0.001371433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002935781,"about_ca_system_score_gemma":0.00004872826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000026184,"about_ca_topic_score_gemma":0.00003731647,"domain_scores_codex":[0.9988406,0.00003691298,0.0002717744,0.0004569451,0.000242509,0.0001512744],"domain_scores_gemma":[0.9988317,0.00002591174,0.0001503171,0.0008878344,0.00004965933,0.00005459024],"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":[1.951139e-7,0.00002584669,3.456779e-8,0.0007006642,0.000006738498,0.000002454777,0.00006249428,0.00001684845,0.0000147506,0.0000296695,0.9980049,0.001135436],"study_design_scores_gemma":[0.00005183076,0.000005457672,0.000001804111,0.001095289,0.00001637075,0.000003783788,0.000008378788,0.07499502,0.0000197788,0.0002422983,0.9234282,0.0001317716],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002218381,0.003575558,0.006764373,0.00003258164,0.0002302352,0.0001725196,0.9891762,0.00004192967,0.000004344769],"genre_scores_gemma":[0.000141158,0.00007132824,0.0001379218,0.00002722881,0.00006532079,0.00006344807,0.9994491,0.000007167763,0.00003726294],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07497817,"threshold_uncertainty_score":0.9994061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07209381814899139,"score_gpt":0.3118934366214614,"score_spread":0.23979961847247,"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."}}