{"id":"W4414588291","doi":"10.2139/ssrn.5606943","title":"A functional approach for curve alignment and shape analysis","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Shape analysis (program analysis); Functional data analysis; Active shape model; Context (archaeology); Deformation (meteorology); Rotation (mathematics); Basis (linear algebra); Functional principal component analysis; Curve fitting; Point distribution model","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":[0.00137292,0.001073058,0.0009161945,0.002962815,0.0009156443,0.001701802,0.002065332,0.00189655,0.006422961],"category_scores_gemma":[0.003540881,0.0006241921,0.001383744,0.001896068,0.001661452,0.002352156,0.002558369,0.002093919,0.001754258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007273746,"about_ca_system_score_gemma":0.0007804013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002347059,"about_ca_topic_score_gemma":0.00176686,"domain_scores_codex":[0.999307,0.0002459844,0.00003796194,0.0001169282,0.0002471175,0.00004503223],"domain_scores_gemma":[0.9990327,0.0003996715,0.00007505735,0.0001411527,0.0002768527,0.00007454018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002506507,0.00005881122,0.0002836215,0.0001396702,0.00004365247,0.00008679045,0.000112477,0.07591538,0.006421796,0.8121688,0.002949158,0.1017949],"study_design_scores_gemma":[0.000003931559,0.00002807735,0.0001617326,0.00002106614,0.00001174219,0.00007865166,0.00002867181,0.7117292,0.001015068,0.2797016,0.007203001,0.00001725095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00160605,0.0001365412,0.9951562,0.00009770617,0.00004848934,0.00001022894,0.00002584146,0.00007424825,0.002844651],"genre_scores_gemma":[0.1982832,0.001439859,0.765251,0.000355554,0.0006225924,0.00022981,0.0003960149,0.001345967,0.03207592],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006422961,"threshold_uncertainty_score":0.02148694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025355929424862,"score_gpt":0.2479919223662127,"score_spread":0.2377383630719641,"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."}}