{"id":"W4414015725","doi":"10.11159/mvml25.002","title":"Human AI - How Big Data is Big Enough?","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data science; 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":[0.03021058,0.001199767,0.001808583,0.003460334,0.004583413,0.02248167,0.00400349,0.009350438,0.01289894],"category_scores_gemma":[0.08956546,0.001070905,0.0009031271,0.004595907,0.01993911,0.04747029,0.008643295,0.01200416,0.006682768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004386687,"about_ca_system_score_gemma":0.008462708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004390262,"about_ca_topic_score_gemma":0.003765181,"domain_scores_codex":[0.977768,0.01113116,0.0009728521,0.002844246,0.006200072,0.001083705],"domain_scores_gemma":[0.8761607,0.09485654,0.003180248,0.008966371,0.009031741,0.007804343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002008791,0.0001551727,0.006777117,0.002630185,0.000268324,0.0002196025,0.002951707,0.002535885,0.0008848149,0.3319751,0.4100425,0.2413587],"study_design_scores_gemma":[0.00002445241,0.00003653551,0.001282437,0.0016487,0.00003767155,0.0001836864,0.003063114,0.002620785,0.0004320019,0.7183893,0.2722094,0.00007177872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002842751,0.05375326,0.03533737,0.8754192,0.004383468,0.0001154916,0.001141283,0.0006265748,0.02638073],"genre_scores_gemma":[0.2974872,0.1458426,0.1406146,0.3574111,0.02984887,0.00112963,0.003957421,0.001927592,0.02178114],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03021058,"threshold_uncertainty_score":0.1597707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0409612776379997,"score_gpt":0.2537377033176493,"score_spread":0.2127764256796496,"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."}}