{"id":"W7115819204","doi":"","title":"Rapid Model-Based Recipe Design from Limited-Sample Datasets: Experimental Validation in Nanoparticle and Microgel Systems","year":2025,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; McMaster University","keywords":"Reliability (semiconductor); Multicollinearity; Metric (unit); Partial least squares regression; Projection (relational algebra); Latent variable; Inverse; Cluster analysis; Nonlinear system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00911766,0.001305932,0.001117329,0.0006881846,0.0006399793,0.00118337,0.001181298,0.001028235,0.001716738],"category_scores_gemma":[0.01484363,0.0005770293,0.001345987,0.0007167449,0.0008443089,0.0012932,0.001247163,0.002387608,0.0004289232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008598095,"about_ca_system_score_gemma":0.001613415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003585686,"about_ca_topic_score_gemma":0.003784666,"domain_scores_codex":[0.9983813,0.0007412669,0.0001184521,0.0003308217,0.0003603516,0.00006779826],"domain_scores_gemma":[0.9910685,0.006323486,0.0004668664,0.001157057,0.000876804,0.0001072875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004417303,0.0006595501,0.004317675,0.0007874889,0.0001783122,0.0001013874,0.0002442744,0.8969814,0.02582537,0.004128957,0.001092659,0.06524117],"study_design_scores_gemma":[0.00002561071,0.0002110974,0.0007059313,0.00001878312,0.0000148819,0.00001136128,0.00003610439,0.9781731,0.01894123,0.001168472,0.0006735876,0.00001996598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3480346,0.0008101212,0.6448883,0.0003497942,0.00009584725,0.0005439654,0.001136651,0.002384624,0.001756189],"genre_scores_gemma":[0.6301607,0.0004166225,0.3653767,0.0001228745,0.00001820564,0.0008894273,0.001981739,0.0002827519,0.0007511058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00911766,"threshold_uncertainty_score":0.04821938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03873088378580172,"score_gpt":0.2603551752539687,"score_spread":0.221624291468167,"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."}}