{"id":"W4398618100","doi":"10.7910/dvn/k0oyqf/iw3uit","title":"tableA3.txt","year":2019,"lang":"it","type":"dataset","venue":"Harvard Dataverse","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Word (group theory); Ideology; Linguistics; Computer science; Natural language processing; Mathematics; Political science; Philosophy; Politics; Law","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002270796,0.0005655453,0.0009448691,0.0003752279,0.0007514511,0.0004921954,0.001856293,0.0005632218,0.4048578],"category_scores_gemma":[0.0008677292,0.0005680348,0.0005201034,0.001141144,0.0004192133,0.0006601421,0.0008898021,0.0007263959,0.8297902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002530637,"about_ca_system_score_gemma":0.0008263373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004453374,"about_ca_topic_score_gemma":0.0005748307,"domain_scores_codex":[0.9946731,0.001117545,0.0007405079,0.001129588,0.001519926,0.0008193833],"domain_scores_gemma":[0.9961444,0.001013274,0.000617586,0.001526647,0.0003046704,0.000393386],"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":[0.00003638969,0.0001748994,0.00006659534,0.0001048701,0.0003402554,0.0000515768,0.000365414,0.0001907371,0.000005507287,0.001781484,0.9943821,0.002500143],"study_design_scores_gemma":[0.0004098208,0.00005350396,0.0001554769,0.0001083636,0.0006757673,0.000003861023,0.001009883,0.0006775172,0.000002711511,0.0005246731,0.9956914,0.0006869931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004033427,0.000002859484,0.0009120843,0.00004726496,0.0030612,0.000450942,0.9849895,0.00005080244,0.01044501],"genre_scores_gemma":[0.0001119173,0.001081841,0.001937127,0.0007638678,0.001589325,0.00001547956,0.9622068,0.00003261978,0.03226103],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4249324,"threshold_uncertainty_score":0.9996771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04761380894429166,"score_gpt":0.3379394933953652,"score_spread":0.2903256844510735,"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."}}