{"id":"W4292156489","doi":"10.1007/b98888","title":"Functional Data Analysis","year":2005,"lang":"en","type":"book","venue":"Springer series in statistics","topic":"Scientific Measurement and Uncertainty Evaluation","field":"Decision Sciences","cited_by":3585,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Royal Society; Foundation for the National Institutes of Health; National Science Foundation","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002447101,0.001379686,0.001332784,0.002444973,0.0004692385,0.002038141,0.001146064,0.0009952774,0.03653064],"category_scores_gemma":[0.005569656,0.000732325,0.001395275,0.002027928,0.001146027,0.001919428,0.001363108,0.001728177,0.01778724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006532313,"about_ca_system_score_gemma":0.0006625702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001246342,"about_ca_topic_score_gemma":0.001432896,"domain_scores_codex":[0.9989464,0.0002777898,0.0000936299,0.0002538778,0.0003988676,0.00002955418],"domain_scores_gemma":[0.9981539,0.0008890124,0.00005206251,0.0005213031,0.0003527131,0.00003096899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002097479,0.00001805505,0.0002049681,0.0003098293,0.00006876018,0.0000555156,0.00008198956,0.006844514,0.00104578,0.2207886,0.1241615,0.6463995],"study_design_scores_gemma":[0.00001104452,0.00003540075,0.0006703926,0.0002421794,0.00006149126,0.0004658149,0.00005643681,0.07598015,0.002200444,0.5689845,0.3512461,0.00004603388],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003662491,0.002657168,0.9601019,0.0005766695,0.0004533813,0.00003828904,0.0006322287,0.001503761,0.03367031],"genre_scores_gemma":[0.03351306,0.00703989,0.8018918,0.001087551,0.001181968,0.0004016439,0.003807585,0.002755115,0.1483215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03653064,"threshold_uncertainty_score":0.1222072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4218189557546074,"score_gpt":0.4366165447251047,"score_spread":0.01479758897049732,"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."}}