{"id":"W6979301470","doi":"","title":"MuseScorer: Idea Originality Scoring At Scale","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Creativity in Education and Neuroscience","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Originality; Scale (ratio); Creativity; Process (computing); Measure (data warehouse); Cluster analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007775579,0.001380883,0.0008824811,0.005872864,0.000608665,0.002850903,0.001456441,0.0009903399,0.01616979],"category_scores_gemma":[0.05853251,0.0003920445,0.001238192,0.002984499,0.0007149462,0.003102626,0.004250494,0.001137329,0.00951624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005113225,"about_ca_system_score_gemma":0.0008157903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005739393,"about_ca_topic_score_gemma":0.001643255,"domain_scores_codex":[0.9936227,0.001971487,0.0008044379,0.001036533,0.00236878,0.0001961316],"domain_scores_gemma":[0.9702932,0.01479556,0.003511602,0.004635633,0.005726182,0.001037913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00197574,0.0004230708,0.05688308,0.003785704,0.0004367812,0.0003113569,0.005331909,0.001902888,0.02444481,0.01094592,0.1874407,0.7061181],"study_design_scores_gemma":[0.001258052,0.00202171,0.3133882,0.001488863,0.0004963463,0.002361181,0.006763481,0.1122078,0.06940007,0.0782781,0.4111138,0.0012224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3225131,0.002780615,0.440304,0.0009342708,0.00118069,0.004241774,0.08988224,0.08677008,0.05139325],"genre_scores_gemma":[0.4228446,0.0007058645,0.4723655,0.0004954284,0.0003123333,0.007643273,0.07171563,0.004902288,0.01901511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01616979,"threshold_uncertainty_score":0.0540933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0724851422035902,"score_gpt":0.398323340635686,"score_spread":0.3258381984320958,"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."}}