{"id":"W2112585725","doi":"10.5539/cis.v7n1p10","title":"A Formal Concept Analysis Approach to Data Mining: The QuICL Algorithm for Fast Iceberg Lattice Construction","year":2013,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Association rule learning; Lattice (music); Formal concept analysis; Algorithm; Lattice Miner; Data mining","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":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0008495229,0.0001162469,0.0001476236,0.0002864238,0.0006709829,0.001776641,0.001991878,0.00003112853,0.000003848671],"category_scores_gemma":[0.00002704577,0.00007531571,0.00003742547,0.001916162,0.0002967861,0.01704695,0.001151997,0.00006119027,0.00002049075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001893606,"about_ca_system_score_gemma":0.0000756407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002873097,"about_ca_topic_score_gemma":5.883103e-7,"domain_scores_codex":[0.9986141,0.00002071853,0.0003201695,0.0003279519,0.0003788103,0.0003382064],"domain_scores_gemma":[0.9985106,0.00009203188,0.0001381413,0.0007943419,0.0003164843,0.000148388],"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":[7.044803e-7,0.000008698232,0.00004680027,0.000004036815,0.00001599832,2.580542e-8,0.003150374,0.0006362159,0.000001098824,0.01165384,0.002062774,0.9824194],"study_design_scores_gemma":[0.0001786936,0.00005600916,0.004651014,0.000002444561,0.0000164698,0.00001793745,0.000442517,0.9877773,0.000009920445,0.0001365048,0.006589413,0.000121787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001510423,0.00001257596,0.9935656,0.0006236103,0.0003179982,0.0004512957,0.00001986649,0.00005728519,0.003441346],"genre_scores_gemma":[0.07593619,0.000004395355,0.9215831,0.002310147,0.00008055177,0.00003703006,0.00003938646,0.000001576276,0.000007643316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9871411,"threshold_uncertainty_score":0.9992596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03053334552154947,"score_gpt":0.2589731668195537,"score_spread":0.2284398212980043,"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."}}