{"id":"W2145719275","doi":"10.5539/ijef.v6n8p15","title":"Big Data and the Dot Com Bubble","year":2014,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Headline; Big data; Computer science; Data science; Advertising; Business; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001708986,0.0003824614,0.0003195784,0.001360069,0.0006577956,0.002571449,0.0006550011,0.001095676,0.003132146],"category_scores_gemma":[0.01158154,0.0003370415,0.0005996841,0.0015623,0.0009380637,0.003150166,0.0009370641,0.0014073,0.000443935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160501,"about_ca_system_score_gemma":0.0009392577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01434602,"about_ca_topic_score_gemma":0.01300252,"domain_scores_codex":[0.999416,0.0002752146,0.00003110506,0.00009451564,0.0001159561,0.00006732817],"domain_scores_gemma":[0.9892483,0.008102769,0.001345757,0.0003111221,0.0005976379,0.0003943914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004154253,0.00042439,0.422939,0.0003217045,0.0004441338,0.0009806966,0.001791451,0.1730159,0.0008418998,0.2933072,0.03352796,0.07199033],"study_design_scores_gemma":[0.00005350061,0.0001104749,0.05816475,0.0001430657,0.00009380511,0.0002041568,0.0007845057,0.7925851,0.0007918307,0.1268555,0.02014943,0.00006385214],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7428222,0.002843863,0.135343,0.06759827,0.0006061505,0.0002248851,0.007527481,0.0006262196,0.042408],"genre_scores_gemma":[0.9865091,0.0006225232,0.007892628,0.0006008346,0.0001374088,0.00008042135,0.001105222,0.00003379189,0.003017968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01434602,"threshold_uncertainty_score":0.02852499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05557067799859348,"score_gpt":0.3057310727535176,"score_spread":0.2501603947549241,"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."}}