{"id":"W2966601220","doi":"10.29173/jjs20","title":"The Uses of Juvenilia","year":2019,"lang":"en","type":"article","venue":"Journal of Juvenilia Studies","topic":"Themes in Literature Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"","keywords":"Construct (python library); Literature; Image (mathematics); History; Aesthetics; Psychology; Art; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000615311,0.0001405825,0.0005343696,0.0001147111,0.0002335214,0.00008412376,0.000369903,0.00002690734,0.0002793111],"category_scores_gemma":[0.0002532391,0.00007371969,0.0003714572,0.00006912887,0.0003995885,0.000255664,0.00008876089,0.0002182785,0.00003436223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003705757,"about_ca_system_score_gemma":0.00003885233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007801188,"about_ca_topic_score_gemma":0.0001303486,"domain_scores_codex":[0.9985521,0.00008141438,0.0007201015,0.0000916336,0.0003803819,0.0001743489],"domain_scores_gemma":[0.9975629,0.0005444161,0.0007563941,0.0002664161,0.0008389663,0.00003085246],"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":[0.0005284327,0.0003001901,0.01064835,0.0003742461,0.008407704,0.00004458065,0.1851621,0.00009266477,0.001409995,0.4933206,0.290911,0.008800138],"study_design_scores_gemma":[0.0003921372,0.0003278021,0.0003777579,0.0001830574,0.000309094,0.00001553718,0.02907636,0.000005478551,0.0006641177,0.008662203,0.9598645,0.0001219372],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759556,0.07347766,0.000005973633,0.004362238,0.006490145,0.0001916425,0.00002472333,0.00002094653,0.0394711],"genre_scores_gemma":[0.9762126,0.001129894,0.0001017324,0.0001390955,0.0007134423,0.00000152915,3.299528e-7,0.00001297598,0.02168842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6689535,"threshold_uncertainty_score":0.305826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02654589974634807,"score_gpt":0.2727687254640148,"score_spread":0.2462228257176667,"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."}}