{"id":"W4412408680","doi":"10.1080/10447318.2025.2526580","title":"Task–Technology Fit Leads to Conflict: The Double-Edged-Sword Effect of Generative Artificial Intelligence on Scientific Creative Performance in Humanities and Social Sciences Research","year":2025,"lang":"en","type":"article","venue":"International Journal of Human-Computer Interaction","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"SWORD; Generative grammar; Task (project management); Humanities; Sociology; Psychology; Social psychology; Artificial intelligence; Computer science; Art; Management; Economics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.006941393,0.0001506313,0.0002913746,0.002680112,0.001403448,0.000625127,0.0009676139,0.00009697918,0.00003762829],"category_scores_gemma":[0.0003651303,0.0001163469,0.00007857741,0.00120621,0.001991987,0.0006481862,0.0002006089,0.0006758071,0.000006261364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007103067,"about_ca_system_score_gemma":0.0003130205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004518561,"about_ca_topic_score_gemma":0.0009711527,"domain_scores_codex":[0.9966819,0.0007829986,0.0008418761,0.0003115348,0.001100167,0.0002815623],"domain_scores_gemma":[0.9958806,0.000750494,0.0004625811,0.0001208663,0.00276676,0.00001867532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001048948,0.0003373213,0.01771306,0.00009183776,0.0001677989,0.00001605122,0.09971447,0.003273382,0.003330732,0.8315257,0.001565209,0.04121549],"study_design_scores_gemma":[0.006280857,0.02162135,0.1658437,0.007609374,0.0002004683,0.0001344442,0.247658,0.01964836,0.3005313,0.1397545,0.08840389,0.002313725],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860424,0.00004348043,0.0009974513,0.005218911,0.002626406,0.0004984218,0.000002562633,0.00001348762,0.004556837],"genre_scores_gemma":[0.9985977,0.000006414322,0.00007379182,0.0001218433,0.0006993419,0.00002354508,0.00000234896,0.000006252813,0.0004687599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6917711,"threshold_uncertainty_score":0.9998966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1517882542483035,"score_gpt":0.4832900095697034,"score_spread":0.3315017553213998,"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."}}