{"id":"W308199711","doi":"","title":"Webnotes: Is Google Getting Too Good?","year":2007,"lang":"en","type":"article","venue":"ABA banking journal","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"World Wide Web; Web page; Sentence; Search engine optimization; Computer science; The Internet; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002008126,0.000111272,0.0001137016,0.0002056056,0.000532856,0.0006275902,0.0007466138,0.00006276168,0.0002364868],"category_scores_gemma":[0.00007118815,0.00009330858,0.0001089504,0.0004010752,0.00002657464,0.001313432,0.000155329,0.0004952166,0.0002240672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009443264,"about_ca_system_score_gemma":0.0001119077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007554143,"about_ca_topic_score_gemma":0.00000115899,"domain_scores_codex":[0.9982364,0.00003021113,0.000424832,0.0001382059,0.0006627697,0.0005075824],"domain_scores_gemma":[0.9990856,0.0001089063,0.0001948151,0.000228171,0.0002118025,0.0001707187],"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":[0.00001698257,0.00008356874,0.0116395,0.00001959779,0.00003446615,0.0003391107,0.009543002,0.00004385757,0.002965382,0.03082545,0.008058131,0.9364309],"study_design_scores_gemma":[0.003946617,0.000942064,0.1667893,0.0005082461,0.00004880082,0.009058486,0.001340161,0.04162742,0.0943395,0.02234028,0.6568427,0.002216391],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1822851,0.0001312063,0.7954092,0.001910197,0.000990821,0.00009898635,0.000001334995,0.0001261017,0.01904701],"genre_scores_gemma":[0.9492448,0.00001940022,0.04601631,0.002950846,0.0004530393,8.911937e-7,7.799495e-7,0.000009603079,0.001304311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9342146,"threshold_uncertainty_score":0.6051867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966015173165128,"score_gpt":0.2821559911997701,"score_spread":0.2624958394681188,"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."}}