{"id":"W1875686838","doi":"10.16995/dscn.139","title":"Linking Fancy unto Fancy: Towards a Semantic Codex","year":2009,"lang":"fr","type":"article","venue":"Digital Studies / Le champ numérique","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Meaning (existential); Computer science; Automatic summarization; Hypertext; Reading (process); Representation (politics); Interpretation (philosophy); Dimension (graph theory); Set (abstract data type); Linguistics; Artificial intelligence; Epistemology; Philosophy; World Wide Web; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003112826,0.0008712574,0.0009000911,0.005381078,0.003470875,0.007406753,0.001969259,0.002659618,0.01096923],"category_scores_gemma":[0.01089568,0.0006978811,0.001036943,0.00374912,0.005857489,0.02130225,0.007354128,0.003030565,0.002244462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002128541,"about_ca_system_score_gemma":0.002835117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008283811,"about_ca_topic_score_gemma":0.005648239,"domain_scores_codex":[0.9969239,0.001077747,0.0002691062,0.0007653395,0.000773187,0.0001907694],"domain_scores_gemma":[0.9952958,0.001571699,0.0003654335,0.00120364,0.001322992,0.0002403871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005836328,0.00004177018,0.001937513,0.0001852974,0.0000194899,0.0001820095,0.003134374,0.0009750599,0.001889076,0.9030211,0.0117013,0.07685464],"study_design_scores_gemma":[0.00002102762,0.00003162779,0.001388558,0.0003891533,0.00008065469,0.0004431791,0.003237493,0.03180853,0.007406411,0.592379,0.3627381,0.00007620461],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02065414,0.0004134138,0.9170339,0.005313893,0.000480919,0.0001910774,0.001194033,0.005623478,0.04909519],"genre_scores_gemma":[0.3845378,0.0006589821,0.5786793,0.001391458,0.0003617842,0.0002632853,0.003167677,0.002990337,0.02794955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01096923,"threshold_uncertainty_score":0.03669572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03232175263403574,"score_gpt":0.3017399854489766,"score_spread":0.2694182328149408,"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."}}