{"id":"W1998258485","doi":"10.1023/b:scie.0000045122.93018.2a","title":"Exploring website features for business information","year":2004,"lang":"en","type":"article","venue":"Scientometrics","topic":"Web visibility and informetrics","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Webometrics; Ranking (information retrieval); Data collection; Business; China; Marketing; Computer science; Information retrieval; World Wide Web; Statistics; Political science; Mathematics","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00122144,0.0001185345,0.0001250207,0.004724024,0.0002666374,0.0008469886,0.001031664,0.00005474643,0.000001924129],"category_scores_gemma":[0.002808766,0.0001070775,0.00007024513,0.0349849,0.00004297145,0.009716222,0.0002507407,0.00009948926,0.0001123663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000209114,"about_ca_system_score_gemma":0.0001981809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002878189,"about_ca_topic_score_gemma":0.000003661816,"domain_scores_codex":[0.9982677,0.00000677829,0.0002854616,0.0002329123,0.0008051094,0.0004021049],"domain_scores_gemma":[0.9982566,0.0001370986,0.0001198105,0.0005024792,0.0008417224,0.0001423128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001761821,0.0001662923,0.001312844,0.0002219205,0.00001596967,0.000001785316,0.003234059,0.01164525,0.0001267869,0.4309795,0.002161955,0.5501159],"study_design_scores_gemma":[0.00529793,0.00068072,0.4864403,0.0001084054,0.00002441163,0.00003305542,0.0004914824,0.01392745,0.02318722,0.02732241,0.440958,0.001528614],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05103415,0.0000795457,0.9433129,0.0007295134,0.001854828,0.0003039762,0.00001044352,0.0002122993,0.002462287],"genre_scores_gemma":[0.7692963,0.0001248348,0.229259,0.0009416692,0.0001399807,0.00007281841,0.00002431399,0.000008235394,0.0001329186],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7182621,"threshold_uncertainty_score":0.985527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.122088333432935,"score_gpt":0.283840460132473,"score_spread":0.161752126699538,"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."}}