{"id":"W6939568781","doi":"10.6084/m9.figshare.19367429","title":"Additional file 2 of Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Saskatchewan; Children's Hospital of Eastern Ontario","funders":"","keywords":"Smoothing spline; Spline (mechanical); Trajectory; Monotone cubic interpolation; Nonlinear system; B-spline; Log-linear model; Linear regression; Cubic Hermite spline","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005804014,0.0001293095,0.0003837556,0.0002379321,0.0001134316,0.00001810785,0.00009841094,0.00003139644,0.5146211],"category_scores_gemma":[0.0003483521,0.0001451903,0.00005675809,0.0002990265,0.00001452843,0.0002060642,0.0001975478,0.0001403651,0.00003460801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005944194,"about_ca_system_score_gemma":0.00002310153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670127,"about_ca_topic_score_gemma":0.0001538438,"domain_scores_codex":[0.9990972,0.00001380085,0.0003509274,0.0003263977,0.00005989847,0.0001518087],"domain_scores_gemma":[0.9994006,0.0002175957,0.0001655659,0.0001069847,0.00005864062,0.00005067994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001632088,0.0002512067,0.04255334,0.000479973,0.0006568829,0.00007164993,0.00183111,0.003563354,0.00002454458,0.0001070956,0.9497842,0.0005134665],"study_design_scores_gemma":[0.0008306662,0.0002620207,0.6601395,0.0008645791,0.00006644402,0.00004873841,0.0006512164,0.2325429,0.00003203309,0.0006658021,0.1028211,0.00107501],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1369625,0.001281429,8.140708e-7,0.00002217443,0.00003314585,0.000118532,0.8615493,0.000007964628,0.00002413094],"genre_scores_gemma":[0.2510014,0.00005582087,0.0009101454,0.00009381048,0.0001305615,0.0003429436,0.7473143,0.00001830184,0.0001327305],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8469631,"threshold_uncertainty_score":0.5920687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09946267161335642,"score_gpt":0.2477433717173021,"score_spread":0.1482807001039457,"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."}}