{"id":"W2810393426","doi":"10.1093/llc/fqz011","title":"Beyond validation: Using programmed diagnostics to learn about, monitor, and successfully complete your DH project","year":2019,"lang":"en","type":"article","venue":"Digital Scholarship in the Humanities","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"","keywords":"Computer 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000673489,0.0001972559,0.0001976446,0.0001794923,0.0003344761,0.005392266,0.000811057,0.00005302979,0.000004018562],"category_scores_gemma":[0.0001788791,0.0001562918,0.00004886237,0.0002954899,0.00006529237,0.001911535,0.0002858957,0.0003537348,0.00006966662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007126741,"about_ca_system_score_gemma":0.00004941038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001414326,"about_ca_topic_score_gemma":0.00001242654,"domain_scores_codex":[0.9983658,0.0001630722,0.0002874483,0.000353825,0.0004464389,0.0003834077],"domain_scores_gemma":[0.9990596,0.0003010656,0.0001101949,0.0003537155,0.0001381735,0.00003722539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002640022,0.0001662571,0.3452043,0.000212281,0.00005148614,0.00008063677,0.04172755,0.00085832,0.0003096178,0.592737,0.00004772643,0.01857836],"study_design_scores_gemma":[0.002521985,0.00260568,0.3849432,0.003527724,0.00006895248,0.0005020389,0.03838481,0.005369139,0.002510064,0.03056639,0.5247795,0.004220486],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914211,0.0002906587,0.002122644,0.00008768356,0.0004306966,0.0007468251,0.000008704881,0.00009326484,0.004798407],"genre_scores_gemma":[0.9967859,0.000005431272,0.000680285,0.0002128902,0.0001825697,0.00003440227,0.000007339333,0.00001800259,0.002073113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5621706,"threshold_uncertainty_score":0.9956402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09576558282943255,"score_gpt":0.305451720361224,"score_spread":0.2096861375317914,"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."}}