{"id":"W4297813146","doi":"10.48550/arxiv.1707.03471","title":"Proceedings of the 2017 AdKDD & TargetAd Workshop","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nova scotia; Conjunction (astronomy); Library science; Computer science; History; Physics; Archaeology; Astronomy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01714157,0.002034884,0.004030596,0.004331872,0.002709684,0.01256177,0.00324067,0.002641413,0.02679101],"category_scores_gemma":[0.02642507,0.001339062,0.001690528,0.004137191,0.002166698,0.01074873,0.006330521,0.006937275,0.03036007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005081498,"about_ca_system_score_gemma":0.0133128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01917661,"about_ca_topic_score_gemma":0.03515904,"domain_scores_codex":[0.9902801,0.002480897,0.0006781619,0.001326187,0.004804476,0.0004302474],"domain_scores_gemma":[0.9768199,0.00711528,0.0003642693,0.004046264,0.008199269,0.003454974],"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":[0.0001335954,0.0001101944,0.000355936,0.0001545039,0.00004164406,0.00007195517,0.00007993703,0.0007732704,0.0002896327,0.003772747,0.9407772,0.05343924],"study_design_scores_gemma":[0.00006842859,0.00003082557,0.0006246183,0.0001681117,0.00004320354,0.0001445503,0.0002131686,0.009494492,0.001625629,0.01622395,0.9713181,0.00004492543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01828849,0.05420886,0.3972495,0.1875826,0.1372468,0.001412624,0.09030335,0.03321051,0.08049735],"genre_scores_gemma":[0.0570394,0.06047787,0.2619102,0.02052972,0.02191109,0.0016632,0.3383614,0.01201856,0.2260886],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.973209,"threshold_uncertainty_score":0.09065437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1160947476379872,"score_gpt":0.2187466969268252,"score_spread":0.1026519492888379,"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."}}