{"id":"W2627710665","doi":"10.1145/772862.772887","title":"Multi-relational data mining","year":2002,"lang":"en","type":"article","venue":"ACM SIGKDD Explorations Newsletter","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Knowledge extraction; Data science; Relational database; Data mining; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006857553,0.001218159,0.001647424,0.005641037,0.001064944,0.005854344,0.003925705,0.001098868,0.005143336],"category_scores_gemma":[0.02124682,0.0006189688,0.001897475,0.009295062,0.0007344011,0.009080381,0.003884666,0.002009049,0.00588246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008066392,"about_ca_system_score_gemma":0.001640217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009818592,"about_ca_topic_score_gemma":0.001252073,"domain_scores_codex":[0.9904523,0.001955686,0.001170302,0.002036065,0.004117121,0.0002684682],"domain_scores_gemma":[0.9893662,0.00481165,0.0008931778,0.002504222,0.002101863,0.0003228285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001303465,0.0001803224,0.007866713,0.002610154,0.0005474271,0.001015412,0.0003367455,0.007883908,0.003798897,0.07670861,0.04730609,0.8516154],"study_design_scores_gemma":[0.00005584606,0.0002371599,0.004233899,0.001054388,0.0005908032,0.007599789,0.0007719019,0.1293656,0.01538532,0.2542057,0.5863222,0.0001773451],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003711064,0.02772629,0.9485956,0.003167174,0.0007881157,0.0005365558,0.003351207,0.00255208,0.009572045],"genre_scores_gemma":[0.06739901,0.02847978,0.8844896,0.001813847,0.001195457,0.0004931945,0.01004433,0.0003927262,0.00569206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006857553,"threshold_uncertainty_score":0.03626668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2564192870307092,"score_gpt":0.3081369896490975,"score_spread":0.05171770261838832,"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."}}