{"id":"W37717759","doi":"10.1016/j.scitotenv.2023.167102","title":"From Usenet to CoWebs - Interacting with social information spaces.","year":2003,"lang":"en","type":"article","venue":"Educational Technology & Society","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Knowledge management; Sociology; Multimedia; Mathematics education; Human–computer interaction; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002126892,0.001018526,0.0007106775,0.001681816,0.001028026,0.002956404,0.001674724,0.001328271,0.04773652],"category_scores_gemma":[0.005964729,0.0005683825,0.0007930559,0.001790539,0.0005671254,0.007770361,0.006800955,0.001005157,0.01999114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051116,"about_ca_system_score_gemma":0.001071108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01905296,"about_ca_topic_score_gemma":0.03205886,"domain_scores_codex":[0.9985664,0.0004275925,0.0001386741,0.0002787867,0.0004096562,0.0001789601],"domain_scores_gemma":[0.9978305,0.0007574746,0.000119853,0.0006213518,0.0002213542,0.0004494591],"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":[0.001025163,0.0003031156,0.007873976,0.00133109,0.0001821065,0.0005470172,0.002176828,0.003357894,0.005077319,0.04217688,0.6108713,0.3250773],"study_design_scores_gemma":[0.00007753376,0.0001221642,0.006031231,0.000318279,0.00003695602,0.0002014968,0.001155821,0.02889046,0.002231469,0.02728538,0.9335704,0.00007872974],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06368444,0.008255241,0.1345782,0.01290623,0.001596869,0.002223918,0.2799162,0.2479855,0.2488533],"genre_scores_gemma":[0.3457302,0.005247085,0.1378103,0.003388521,0.0004481804,0.00278309,0.3510126,0.01595766,0.1376225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04773652,"threshold_uncertainty_score":0.1596946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885637417685463,"score_gpt":0.3355320605489936,"score_spread":0.3166756863721389,"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."}}