{"id":"W1483930064","doi":"10.22230/src.2013v4n3a123","title":"Reading Environments for Genetic Editions","year":2013,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reading (process); Computer science; Presentation (obstetrics); Digital humanities; Philology; Set (abstract data type); World Wide Web; Documentation; State (computer science); Close reading; Linguistics; Literature; Art; Sociology; Philosophy; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008470521,0.00007133483,0.00007419494,0.0001260936,0.001957594,0.00393638,0.0003474435,0.0000415586,0.0008249381],"category_scores_gemma":[0.0003558069,0.00006296853,0.00003296732,0.00002839973,0.0004859989,0.00334286,0.000174825,0.0004118831,0.0002077795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003743156,"about_ca_system_score_gemma":0.00002047123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002677597,"about_ca_topic_score_gemma":0.0001155871,"domain_scores_codex":[0.9990028,0.0001664462,0.0001578358,0.0001422574,0.0002762417,0.0002544158],"domain_scores_gemma":[0.9988158,0.0003360854,0.00003191697,0.0004116389,0.0002861028,0.0001184087],"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":[0.00001176904,0.0001253291,0.0004053793,0.00003441503,0.00003022609,3.161225e-7,0.01026205,6.536129e-7,0.0004798933,0.9304824,0.03331452,0.02485306],"study_design_scores_gemma":[0.0002468255,0.0001366204,0.005552241,0.00005003289,0.000005925952,0.000001315829,0.006654446,0.00007668788,0.00005625107,0.1675451,0.8195555,0.0001191127],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6235856,0.002835408,0.0001860945,0.009859524,0.0002608433,0.002104703,0.00009649059,0.00009647478,0.3609749],"genre_scores_gemma":[0.9720016,0.0004451983,0.0006799338,0.0001962963,0.0002138966,0.0004219883,0.0000704236,0.00001526525,0.02595538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7862409,"threshold_uncertainty_score":0.9993417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1471699120763154,"score_gpt":0.3276753681374433,"score_spread":0.1805054560611279,"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."}}