{"id":"W4245969647","doi":"10.26434/chemrxiv.14317706","title":"Computational Prediction of the Supramolecular Self-Assembling Properties of Organic Molecules: Flexibility vs Rigidity","year":2021,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Supramolecular Self-Assembly in Materials","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Fonds De La Recherche Scientifique - FNRS","keywords":"Supramolecular chemistry; Molecule; Monomer; Hydrogen bond; Amide; Flexibility (engineering); Rigidity (electromagnetism); Materials science; Computational chemistry; Covalent bond; Chemistry; Chemical physics; Nanotechnology; Crystallography; Computer science; Mathematics; Polymer; Organic chemistry","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":[0.0006629548,0.000589117,0.0007219693,0.0006163369,0.000368703,0.0007323013,0.0006562956,0.001469115,0.001940413],"category_scores_gemma":[0.002616966,0.0003843939,0.0005232348,0.0005172978,0.000558538,0.0004753531,0.0004016766,0.0007183323,0.0001747047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006587521,"about_ca_system_score_gemma":0.0008577016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005241061,"about_ca_topic_score_gemma":0.004887281,"domain_scores_codex":[0.9999045,0.0000398858,0.000004819208,0.00001703852,0.00001339751,0.00002044033],"domain_scores_gemma":[0.9975453,0.002091958,0.00009576405,0.00007028915,0.000095993,0.0001006797],"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":[0.00006582291,0.00004330556,0.0007184524,0.00003520174,0.00001937517,0.00003388625,0.000007481256,0.9952946,0.0002788597,0.001294979,0.000222009,0.00198599],"study_design_scores_gemma":[0.000006856196,0.000008078657,0.00005789526,0.000001190591,0.000001797576,0.000001182528,0.000002012965,0.999472,0.0001195943,0.0003036123,0.00002502337,8.846278e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542959,0.0004905086,0.03697737,0.0008201136,0.00007968573,0.00005712746,0.0006664215,0.0004829683,0.006130034],"genre_scores_gemma":[0.9804235,0.0001203202,0.01784346,0.00007782615,0.0000219025,0.0001005402,0.0004743181,0.00006053418,0.0008776702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005241061,"threshold_uncertainty_score":0.0104211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02966527766305367,"score_gpt":0.2502468226439208,"score_spread":0.2205815449808671,"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."}}