{"id":"W4391380689","doi":"10.1007/s11071-024-09288-2","title":"Distinguishing periodic attitude motions from Poincaré sections using a compatible clustering method","year":2024,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cluster analysis; Spacecraft; Poincaré conjecture; Invariant (physics); Boundary (topology); Poincaré map; Outlier; Chaotic; Computer science; Mathematics; Control theory (sociology); Mathematical analysis; Algorithm; Physics; Artificial intelligence; Engineering; Aerospace engineering; Bifurcation","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":[0.0006468155,0.0005580237,0.0005561347,0.001505409,0.0006866775,0.0006994774,0.0009806112,0.0008042641,0.001462359],"category_scores_gemma":[0.002407948,0.0003271196,0.0005968033,0.001128328,0.0005416276,0.0007514764,0.0007639072,0.0005442314,0.0007217846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002890597,"about_ca_system_score_gemma":0.0005545351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002485905,"about_ca_topic_score_gemma":0.002569803,"domain_scores_codex":[0.9995393,0.0001187691,0.00002808836,0.0001671197,0.00009923168,0.000047531],"domain_scores_gemma":[0.9986298,0.0004764623,0.00015851,0.0003297856,0.0003114042,0.00009397716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000646394,0.0003075919,0.01384119,0.0002048279,0.000294144,0.0003734623,0.0003438711,0.3053081,0.0964859,0.07153334,0.006335949,0.5043252],"study_design_scores_gemma":[0.0000100108,0.00004487048,0.002849667,0.000005867159,0.0000208434,0.00007331617,0.00003194782,0.9794934,0.004181356,0.0119589,0.001307308,0.00002251101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06166675,0.00009003688,0.9361445,0.0000391736,0.00003203341,0.00003801734,0.0001007815,0.0003582159,0.001530634],"genre_scores_gemma":[0.6671191,0.0001488463,0.3285322,0.00006089947,0.00008781198,0.00008824061,0.001001028,0.0002259712,0.002735984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002485905,"threshold_uncertainty_score":0.004942894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02027740638681995,"score_gpt":0.3008583275352263,"score_spread":0.2805809211484064,"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."}}