{"id":"W7154046087","doi":"10.1145/3772318.3809078","title":"10.1145/3772318.3809078","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Access Control and Trust","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Information privacy; Patient privacy; Privacy protection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002130564,0.002668265,0.001923206,0.002743937,0.002534906,0.005066669,0.0025781,0.004993143,0.9459273],"category_scores_gemma":[0.004021029,0.001553787,0.001233695,0.008964066,0.001567732,0.01079084,0.005884281,0.002280315,0.9644903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002278544,"about_ca_system_score_gemma":0.001216402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01477944,"about_ca_topic_score_gemma":0.0119739,"domain_scores_codex":[0.9992537,0.00006574466,0.00006694099,0.0002038341,0.0002632501,0.0001465001],"domain_scores_gemma":[0.9981039,0.0005080452,0.00008282094,0.0005996188,0.0004036438,0.000302061],"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":[0.0001985558,0.000147479,0.0006408922,0.0006138908,0.00003986883,0.0002171244,0.0001344239,0.0005977688,0.0009039835,0.009951195,0.6727203,0.3138345],"study_design_scores_gemma":[0.00002808029,0.00002317847,0.0008472563,0.0002623492,0.00003631636,0.0001478545,0.00009508423,0.0006530657,0.0003779899,0.002294321,0.9952055,0.00002894727],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001742917,0.004388621,0.009877943,0.00176466,0.002180852,0.0002845505,0.01314891,0.009710523,0.9569011],"genre_scores_gemma":[0.004667757,0.002559586,0.002337201,0.0006556044,0.0001782933,0.0001752088,0.007339355,0.001875307,0.9802116],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05407274,"threshold_uncertainty_score":0.07712811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007098120862960807,"score_gpt":0.2205285132090493,"score_spread":0.2134303923460885,"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."}}