{"id":"W3176329926","doi":"10.4000/jtei.4352","title":"Distributed Text Services (DTS): A Community-Built API to Publish and Consume Text Collections as Linked Data","year":2023,"lang":"en","type":"article","venue":"Journal of the Text Encoding Initiative","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tyndale University","funders":"","keywords":"JSON; Computer science; Serialization; Metadata; XML; Interoperability; World Wide Web; Key (lock); Information retrieval; Database; Programming language; Operating system","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":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001368543,0.0002226526,0.0003655877,0.0003611946,0.002476937,0.0029308,0.001474196,0.00006451836,0.0006265651],"category_scores_gemma":[0.00109134,0.0001583216,0.000120785,0.0004455572,0.0003539348,0.002316405,0.001077611,0.0009935949,0.0001049508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024647,"about_ca_system_score_gemma":0.0001668944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003970062,"about_ca_topic_score_gemma":0.003499116,"domain_scores_codex":[0.9980723,0.0003909058,0.0005793313,0.0001741758,0.0004243292,0.0003590147],"domain_scores_gemma":[0.9969358,0.001207016,0.000488812,0.0005590081,0.0006170039,0.0001923714],"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":[0.0004469224,0.0006611805,0.0025282,0.00031089,0.001401357,0.0001306721,0.3415002,0.0001102365,0.0001772508,0.1555667,0.493285,0.003881379],"study_design_scores_gemma":[0.001038524,0.0005187106,0.004690692,0.0007734756,0.0001818145,0.0001301092,0.1767004,0.0001652612,0.00004312275,0.02515719,0.7901883,0.0004123136],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.679822,0.0002638617,0.00001481526,0.006208271,0.001881743,0.0004883249,0.002563369,0.0001495343,0.3086081],"genre_scores_gemma":[0.9844383,0.00006720635,0.00002692525,0.001927483,0.0004585598,0.000008586704,0.0001008602,0.00002900149,0.01294305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3046163,"threshold_uncertainty_score":0.9988217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1675940492920546,"score_gpt":0.312082648362539,"score_spread":0.1444885990704844,"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."}}