{"id":"W2962883236","doi":"","title":"Nucleation-free $3D$ rigidity","year":2013,"lang":"en","type":"article","venue":"Smith ScholarWorks (Smith College)","topic":"Structural Analysis and Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Computing and Communication Foundations; Directorate for Computer and Information Science and Engineering; National Institute of General Medical Sciences; Defense Advanced Research Projects Agency; McGill University; National Science Foundation","keywords":"Rigidity (electromagnetism); Nucleation; Enhanced Data Rates for GSM Evolution; Combinatorics; Mathematics; Discrete mathematics; Computer science; Physics; Artificial intelligence; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001601689,0.0002966718,0.0003165115,0.0001783187,0.0002953355,0.0002887071,0.0004642739,0.0002087926,0.002755611],"category_scores_gemma":[0.00009923314,0.0002600307,0.0001373338,0.0008276357,0.00004793295,0.001050993,0.0000883168,0.0004659978,0.0005522907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430935,"about_ca_system_score_gemma":0.0000355751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000597579,"about_ca_topic_score_gemma":0.00002276707,"domain_scores_codex":[0.9984329,0.00004568719,0.0004065346,0.0003219847,0.0003739621,0.000418936],"domain_scores_gemma":[0.9987742,0.00006123236,0.00007141344,0.0006647326,0.0002275843,0.0002008841],"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":[0.00003028745,0.00007564544,0.02717975,0.0001819823,0.0005372836,0.00002029184,0.0003275607,0.5046523,0.0004672049,0.003628672,0.4328538,0.03004527],"study_design_scores_gemma":[0.001541103,0.000056147,0.1833363,0.0001467202,0.0001476091,0.00001833814,0.000245876,0.777794,0.0008162935,0.003199011,0.0316638,0.001034828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8741469,0.004213303,0.0355215,0.001461348,0.00254581,0.001628462,0.0001477013,0.002211842,0.07812318],"genre_scores_gemma":[0.9757526,0.0003373018,0.02040501,0.0001962782,0.000371679,0.0000754158,0.00001906448,0.00007715895,0.002765511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.40119,"threshold_uncertainty_score":0.9999852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003564838649793182,"score_gpt":0.1649942120696367,"score_spread":0.1614293734198436,"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."}}