{"id":"W4394181886","doi":"10.6084/m9.figshare.22561216","title":"Artifiical Intelligence in Online Retail","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Computer science; Data science; Advertising","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001030585,0.00033963,0.0003632147,0.0005592183,0.00006161345,0.0002601104,0.0009306115,0.0002737638,0.2512159],"category_scores_gemma":[0.003258398,0.0003362431,0.000138238,0.001140659,0.00001559441,0.0003128509,0.0008980285,0.0007049391,0.3793419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005252759,"about_ca_system_score_gemma":0.00005914884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004453876,"about_ca_topic_score_gemma":0.00928362,"domain_scores_codex":[0.9982241,0.00001145879,0.0004633026,0.0005610095,0.0003013917,0.0004387817],"domain_scores_gemma":[0.998807,0.0002074051,0.0002084961,0.0005194715,0.0002394697,0.00001816994],"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":[0.000007479921,0.00009307029,0.000008392768,0.0007676385,0.000007944258,0.0002254352,0.000001925928,0.000008378763,2.498132e-7,0.000030281,0.9940375,0.004811721],"study_design_scores_gemma":[0.00003306086,0.000005908221,0.0003091333,0.004277884,0.00001294405,0.000001364855,0.00003496331,0.0006738496,0.000004226752,0.0003790877,0.9938807,0.0003868355],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000003545515,0.0001767637,7.057343e-7,0.000119207,0.0004021635,0.0002441232,0.9974404,0.0001283501,0.001484752],"genre_scores_gemma":[0.0000207929,0.00002866827,0.000003776355,0.0007107314,0.00237249,0.0001299171,0.9958633,0.00003804467,0.0008322707],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.128126,"threshold_uncertainty_score":0.999909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1083749308518145,"score_gpt":0.3069499128574868,"score_spread":0.1985749820056723,"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."}}