{"id":"W6966759306","doi":"10.48448/9v3g-p168","title":"Text Characterization Toolkit","year":2022,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Spurious relationship; Scripting language; Characterization (materials science)","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":[0.0008963633,0.0003454133,0.0003039326,0.001638778,0.0003986214,0.0002350475,0.001536166,0.0001355014,0.08699828],"category_scores_gemma":[0.0001905402,0.0003433414,0.00005393936,0.002803657,0.0009679458,0.0003439366,0.0005955964,0.0003796275,0.01441416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006229571,"about_ca_system_score_gemma":0.0008978382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001153794,"about_ca_topic_score_gemma":0.0001247419,"domain_scores_codex":[0.9964749,0.00007020659,0.0002952686,0.0009560513,0.001579236,0.0006243825],"domain_scores_gemma":[0.9983249,0.00002363359,0.0004547977,0.0009275772,0.00008960087,0.0001794308],"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":[0.00001474194,0.0003161951,0.0007726271,0.00005619229,0.00004158787,0.00003778499,0.0002512601,0.00003066856,0.1338534,0.01282352,0.8139276,0.03787445],"study_design_scores_gemma":[0.0001903739,0.00005014933,0.0006243122,0.00003018075,0.00002088569,0.00001437408,0.00005695965,0.002044716,0.000129494,0.00007745856,0.9963223,0.0004387465],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004549524,0.00008386777,0.0007678499,0.0002582919,0.001471599,0.0006494717,0.0009398438,0.001299591,0.9940745],"genre_scores_gemma":[0.004253013,0.00003566712,0.002078361,0.000586769,0.000740306,0.00006385276,0.00206913,0.001248777,0.9889241],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1823947,"threshold_uncertainty_score":0.9999018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01760162032816789,"score_gpt":0.2747537224464708,"score_spread":0.257152102118303,"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."}}