{"id":"W7154016519","doi":"10.1145/3772318.3809057","title":"10.1145/3772318.3809057","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Component (thermodynamics); Data collection","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":[0.002148688,0.003906792,0.002712094,0.003300201,0.002711805,0.005866976,0.003127048,0.005208592,0.938177],"category_scores_gemma":[0.003496429,0.002100034,0.001498642,0.01089346,0.00171839,0.01105921,0.006558589,0.003128537,0.9622653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002546815,"about_ca_system_score_gemma":0.001346801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02129098,"about_ca_topic_score_gemma":0.01489633,"domain_scores_codex":[0.9991241,0.00005988215,0.00007383649,0.0002508039,0.0003100934,0.0001812571],"domain_scores_gemma":[0.9980559,0.0004034604,0.00007927093,0.0006570742,0.0004524454,0.0003518645],"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":[0.0002532214,0.0001860515,0.0004853147,0.0005823895,0.00005223417,0.000217003,0.0001059879,0.0007444935,0.001435824,0.006367194,0.6930141,0.2965561],"study_design_scores_gemma":[0.00004153077,0.00003548837,0.0008347395,0.0002820552,0.00005682806,0.0001567998,0.00009065211,0.001073218,0.0006444221,0.001778977,0.994964,0.00004138716],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002591949,0.006374837,0.01840322,0.001641553,0.002825335,0.0005789672,0.01949881,0.02503769,0.9230477],"genre_scores_gemma":[0.004404527,0.003073374,0.003001487,0.0008054668,0.0001920231,0.0002574991,0.01130646,0.003014453,0.9739447],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06182301,"threshold_uncertainty_score":0.08818293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003335681061711,"score_gpt":0.223380767077721,"score_spread":0.2133474102671039,"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."}}