{"id":"W1491869896","doi":"10.1108/09504120410543129","title":"PIKA: Canadian Children's Literature Database","year":2004,"lang":"en","type":"article","venue":"Reference Reviews","topic":"Themes in Literature Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pika; History; Library science; Database; Geography; Archaeology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002384864,0.002492986,0.003077963,0.1002293,0.006647061,0.008410941,0.004477827,0.001722132,0.2253945],"category_scores_gemma":[0.0246813,0.001116753,0.001873691,0.1619146,0.001195689,0.003093928,0.00286507,0.001709052,0.05661936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04495287,"about_ca_system_score_gemma":0.2537878,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9548502,"about_ca_topic_score_gemma":0.9704193,"domain_scores_codex":[0.9957652,0.0001885497,0.00113165,0.0002692512,0.002053865,0.0005915276],"domain_scores_gemma":[0.9605858,0.002797345,0.002990526,0.0007024162,0.03015857,0.002765376],"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":[0.00008455248,0.00001465374,0.001646674,0.01077278,0.00007337309,0.0001172355,0.000269927,0.00006380196,0.00009295258,0.002046639,0.941076,0.04374146],"study_design_scores_gemma":[0.00003459571,0.0000079908,0.009895362,0.006614686,0.0002228955,0.00009116625,0.0005281653,0.00005250702,0.0001106201,0.0004018721,0.9819818,0.00005828933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0008416426,0.0198392,0.0002348063,0.001544255,0.000363776,0.0005080554,0.9214302,0.0006899563,0.05454818],"genre_scores_gemma":[0.01645603,0.09991659,0.009003825,0.001560253,0.000317674,0.003427849,0.7570277,0.0008236597,0.1114663],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915891,"threshold_uncertainty_score":0.7540197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03844858352952334,"score_gpt":0.2596197167702551,"score_spread":0.2211711332407318,"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."}}