{"id":"W3162606703","doi":"10.1002/jcc.26551","title":"<scp>QSARINS</scp>‐Chem standalone version: A new platform‐independent software to profile chemicals for physico‐chemical properties, fate, and toxicity","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"European Chemical Industry Council","keywords":"Computer science; Software; Profiling (computer programming); Suite; Aquatic toxicology; In silico; Software tool; Chemical toxicity; Software engineering; Biochemical engineering; Environmental chemistry; Chemistry; Operating system; Toxicity; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004239955,0.0002662563,0.0004586071,0.00006400633,0.000120534,0.0002568366,0.0006100135,0.0001298287,0.00001943076],"category_scores_gemma":[0.001164398,0.0002568078,0.0002147736,0.0003951948,0.00005304595,0.0006178712,0.0004884157,0.0003419873,0.000005549376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002691258,"about_ca_system_score_gemma":0.001622865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001596727,"about_ca_topic_score_gemma":1.695783e-7,"domain_scores_codex":[0.9974689,0.00003743515,0.0006806648,0.0004687958,0.001013281,0.0003308955],"domain_scores_gemma":[0.9968011,0.000956557,0.0003967318,0.0002294503,0.001147926,0.0004682722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002357155,0.0008438753,0.0001805078,0.000610106,0.0003676036,0.0001308608,0.001208778,0.1824487,0.761892,0.0006654069,0.03292254,0.01849396],"study_design_scores_gemma":[0.001826367,0.0001071805,0.0003377581,0.0002038008,0.00003218803,0.0007263562,0.00009235646,0.01731962,0.9407577,0.03412417,0.004273803,0.0001987059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5700041,0.0003032116,0.4286249,0.0005852321,0.0001248528,0.0001391516,0.00003653265,0.00003255889,0.0001494024],"genre_scores_gemma":[0.4256892,0.000007425099,0.5723753,0.0005644669,0.00062093,0.0000146804,0.00006190592,0.00002914967,0.0006369538],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1788657,"threshold_uncertainty_score":0.9999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02673511348908201,"score_gpt":0.2745817567170897,"score_spread":0.2478466432280077,"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."}}