{"id":"W4396893084","doi":"10.26434/chemrxiv-2024-zs5xp","title":"Metis - A Python-Based User Interface to Collect Expert Feedback for GenerativeChemistry Models","year":2024,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020","keywords":"Python (programming language); Generative grammar; Computer science; Metis; User interface; Programming language; Interface (matter); Human–computer interaction; Toolbox; World Wide Web; Software engineering; Artificial intelligence; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003290378,0.002858747,0.001368695,0.001255954,0.000567183,0.00202094,0.003435264,0.001465439,0.1138596],"category_scores_gemma":[0.01166688,0.001123598,0.00173163,0.0006903879,0.0008297683,0.002541263,0.00439702,0.002725671,0.03926087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004445,"about_ca_system_score_gemma":0.002167017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001901388,"about_ca_topic_score_gemma":0.003181007,"domain_scores_codex":[0.9987367,0.0003480024,0.000117609,0.0002379286,0.0004352312,0.0001245323],"domain_scores_gemma":[0.9953116,0.002896256,0.000182653,0.0006007364,0.0006951966,0.0003137071],"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":[0.002783529,0.0005993433,0.004889478,0.003085853,0.0003603489,0.001128399,0.001424699,0.0269194,0.01580716,0.02873904,0.7362723,0.1779904],"study_design_scores_gemma":[0.001688581,0.000257584,0.004997435,0.0005278793,0.00008153696,0.0006732226,0.0002113392,0.4309445,0.03777278,0.07458009,0.4478805,0.0003845538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.003404097,0.0001187577,0.308097,0.000463727,0.0001373026,0.0004599733,0.02699764,0.6521105,0.008211122],"genre_scores_gemma":[0.124361,0.0005662045,0.50778,0.002108188,0.0002274917,0.005237125,0.0790604,0.2541305,0.02652911],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1138596,"threshold_uncertainty_score":0.3808983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064793834236246,"score_gpt":0.2578491133890943,"score_spread":0.2372011750467318,"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."}}