{"id":"W2776506588","doi":"10.17605/osf.io/xtukh","title":"PresQT Sept 18, 2017 Workshop","year":2017,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.005329587,0.0004437607,0.0005789321,0.0002259932,0.001069873,0.002273416,0.01399643,0.0002638717,0.1734852],"category_scores_gemma":[0.005828605,0.0004685501,0.000360719,0.0002347131,0.0003445948,0.002790393,0.0124506,0.0006478315,0.8230466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001735232,"about_ca_system_score_gemma":0.0002233878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003114651,"about_ca_topic_score_gemma":0.0001750973,"domain_scores_codex":[0.9935845,0.0004776204,0.000689227,0.003583706,0.0008529989,0.0008119922],"domain_scores_gemma":[0.9737722,0.0004285946,0.0007519462,0.02435178,0.000242473,0.0004530103],"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":[0.00007345575,0.0007092368,0.04274683,0.00009126354,0.0006874392,0.0003369319,0.002022187,0.001613953,0.002860884,0.04002172,0.7345611,0.174275],"study_design_scores_gemma":[0.001306081,0.000001706072,0.122421,0.000177129,0.0001592059,0.0001227895,0.00006741945,0.03095254,0.00937807,0.01912134,0.8149208,0.001371934],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007528174,0.000003063906,0.1074526,0.001810448,0.0007885289,0.0005703287,0.00001392989,0.0003713544,0.8814616],"genre_scores_gemma":[0.4338976,0.0001017819,0.0240127,0.0004101805,0.0002186936,0.000187335,0.00002046243,0.00005215142,0.5410991],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6495614,"threshold_uncertainty_score":0.9997766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03411948240884841,"score_gpt":0.3009844870231003,"score_spread":0.2668650046142519,"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."}}