{"id":"W334537367","doi":"10.4310/cdm.2014.v2014.n1.a4","title":"Introduction to the SK model","year":2014,"lang":"en","type":"preprint","venue":"Current Developments in Mathematics","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008860101,0.0002921531,0.000314256,0.0001929564,0.0001154971,0.0002813048,0.002467739,0.0001119739,0.000006103448],"category_scores_gemma":[0.000151825,0.000203963,0.00004989161,0.0002586583,0.00001958795,0.0001495405,0.004727999,0.0005952564,0.0002194941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001600791,"about_ca_system_score_gemma":0.0002101745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001774144,"about_ca_topic_score_gemma":0.000002884085,"domain_scores_codex":[0.9978481,0.00005481283,0.0005763017,0.0006546557,0.0005543249,0.0003118073],"domain_scores_gemma":[0.9980193,0.00005333502,0.0002327677,0.001508964,0.00009967334,0.00008599601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004560353,0.0006655175,0.0000867869,0.001111496,0.00004903063,0.000003110169,0.01831199,0.172077,0.00001735394,0.0776695,0.2426626,0.487341],"study_design_scores_gemma":[0.00009306864,0.000004558653,0.0001241376,0.0004347722,0.000005087226,0.000002733266,0.00001650521,0.8814734,0.00004666382,0.05796639,0.05952368,0.000309014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001427293,0.0001316301,0.9919764,0.001480368,0.004005125,0.0005442065,0.00000886238,0.00009298181,0.0003331014],"genre_scores_gemma":[0.005715491,0.0001344786,0.9925754,0.0001461952,0.0007252136,0.0002316098,0.00006871864,0.00002576818,0.0003770903],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7093964,"threshold_uncertainty_score":0.8317368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04185444718898296,"score_gpt":0.3061169218620853,"score_spread":0.2642624746731024,"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."}}