{"id":"W7118191717","doi":"10.1145/3731599.3787526","title":"10.1145/3731599.3787526","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Big data; Reduction (mathematics); Data reduction","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002800855,0.000116485,0.0001731064,0.0002409819,0.0001839696,0.0005992662,0.001345491,0.0000294034,0.9960749],"category_scores_gemma":[0.000723201,0.00009052952,0.00007628107,0.001150772,0.00004710554,0.0001900916,0.0003129649,0.00006127022,0.9972981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002134473,"about_ca_system_score_gemma":0.00002198152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002231317,"about_ca_topic_score_gemma":3.438531e-7,"domain_scores_codex":[0.9973357,0.00009190816,0.0003926212,0.0007017585,0.001163276,0.0003147437],"domain_scores_gemma":[0.997915,0.000332501,0.00005216882,0.001402098,0.0001016178,0.00019661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000943636,0.00001557641,3.615611e-7,2.433192e-7,0.000002144675,0.000002514526,0.00001131842,0.0002452752,0.000003352388,0.000003883496,0.4861608,0.5135451],"study_design_scores_gemma":[0.0001121384,0.00004759633,0.0002031957,0.000005523277,0.000004724194,0.000002905926,0.000005415771,0.003928169,0.00001104854,0.0001999826,0.9953517,0.0001275688],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00256184,0.00001760562,0.00004809289,0.0008757998,0.00002825745,0.0001359356,0.00002001807,0.0001319177,0.9961805],"genre_scores_gemma":[0.0009590653,6.501203e-8,0.0005359548,0.0001767369,0.0001057659,0.000004572042,0.000009981594,0.000007945625,0.9981999],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5134175,"threshold_uncertainty_score":0.5778738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05608678229173016,"score_gpt":0.2962160592328205,"score_spread":0.2401292769410903,"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."}}