{"id":"W2273502271","doi":"10.4242/balisagevol8.jordanous01","title":"Contemporary transformation of ancient documents for recording and retrieving maximum information: when one form of markup is not enough","year":2012,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Markup language; Arabic; Computer science; Annotation; RDF; Transformation (genetics); Publication; Information retrieval; World Wide Web; Natural language processing; Linguistics; Artificial intelligence; XML; Semantic Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01261086,0.000449708,0.0004486023,0.003572028,0.004031444,0.007776345,0.00142914,0.002148206,0.0057496],"category_scores_gemma":[0.03477165,0.0003918316,0.0003284374,0.005997979,0.01109446,0.01936673,0.004531808,0.003535293,0.002563658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002916761,"about_ca_system_score_gemma":0.004149251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002852815,"about_ca_topic_score_gemma":0.002907866,"domain_scores_codex":[0.9923578,0.003109853,0.000591511,0.000815914,0.002894515,0.0002304007],"domain_scores_gemma":[0.9740101,0.00937868,0.001266096,0.01074582,0.004222141,0.0003772113],"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":[0.000120602,0.0000658025,0.001568193,0.0008288098,0.00002421907,0.0005771019,0.07192428,0.001255193,0.008359072,0.6033808,0.01680094,0.295095],"study_design_scores_gemma":[0.00001664546,0.0000389839,0.001215053,0.0009636382,0.00003028108,0.001015326,0.02114206,0.001834619,0.01370055,0.1404587,0.8194973,0.0000868231],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1080739,0.009383893,0.4902965,0.03982624,0.003378823,0.000374153,0.001407389,0.00281558,0.3444436],"genre_scores_gemma":[0.5519218,0.007246832,0.386392,0.002520124,0.0006184253,0.0003304609,0.001562005,0.002534736,0.04687366],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01261086,"threshold_uncertainty_score":0.06669337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03342159134163366,"score_gpt":0.2468725924931488,"score_spread":0.2134510011515151,"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."}}