{"id":"W2241545489","doi":"","title":"Emerging Technologies and Repurposing Multimedia: Linkages and Mysteries","year":2009,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Repurposing; Multimedia; Computer science; Emerging technologies; World Wide Web; Artificial intelligence; Engineering","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":[0.003896001,0.0005277568,0.0005567932,0.003485915,0.002538614,0.01848778,0.001436632,0.003331264,0.01040388],"category_scores_gemma":[0.007851921,0.0003869676,0.000347994,0.00414208,0.02034692,0.03848434,0.004339565,0.003312308,0.001205454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001804675,"about_ca_system_score_gemma":0.001782845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001195011,"about_ca_topic_score_gemma":0.001714755,"domain_scores_codex":[0.9983913,0.000664069,0.00007377066,0.0002413257,0.0004335978,0.0001958337],"domain_scores_gemma":[0.9939971,0.003568258,0.0005309389,0.00076917,0.0006957814,0.00043871],"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":[0.00002352614,0.00003724039,0.001891696,0.0002368671,0.00001283886,0.0002096666,0.007607052,0.0002626149,0.0005740147,0.9115841,0.003415592,0.07414481],"study_design_scores_gemma":[0.00001062704,0.00004669593,0.002504495,0.0006762108,0.0000168923,0.0007048099,0.02793154,0.00121516,0.0007953278,0.8297701,0.1362807,0.00004746328],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1682355,0.1970249,0.08286198,0.1379868,0.00279083,0.000142544,0.0005026271,0.0002833091,0.4101715],"genre_scores_gemma":[0.9016985,0.05788845,0.01936433,0.003272057,0.002376112,0.0001097976,0.000116845,0.0001019995,0.01507182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01848778,"threshold_uncertainty_score":0.0348044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03838104005507349,"score_gpt":0.3310077170490144,"score_spread":0.2926266769939409,"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."}}