{"id":"W7116741391","doi":"10.1007/978-3-032-13509-4_14","title":"Shooting Stars: Predicting the NBA Gems of Tomorrow","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in social networks","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Overfitting; Random forest; Interpretability; Feature selection; Robustness (evolution); Feature (linguistics); Estimator; Regression analysis; Support vector machine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006140824,0.0002842981,0.0007358228,0.000174834,0.0002062318,0.00005597576,0.0003588987,0.0006247591,0.0004216589],"category_scores_gemma":[0.00008741817,0.0002662866,0.0002789877,0.0001614989,0.0001317499,0.00004623816,0.0001237659,0.001025769,0.000006613101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001145742,"about_ca_system_score_gemma":0.00004266966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002377269,"about_ca_topic_score_gemma":0.0004183693,"domain_scores_codex":[0.9983128,0.000006703977,0.0008977104,0.0003822042,0.00006889134,0.0003317066],"domain_scores_gemma":[0.9985485,0.0002599491,0.0008285082,0.0002890498,0.00004797024,0.00002600851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006060069,0.00004355701,0.05567624,0.0002739923,0.0004837741,0.0000169391,0.00336641,0.2253304,4.220574e-7,0.6472721,0.004701162,0.06277445],"study_design_scores_gemma":[0.0007274843,0.0000893339,0.004536786,0.0009290687,0.0001237502,0.000002612083,0.00003781725,0.4413208,0.000005147949,0.286533,0.264516,0.00117817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002202794,0.0314477,0.06581528,0.001653883,0.003585229,0.0008796502,0.0003517935,0.00007754208,0.8939861],"genre_scores_gemma":[0.9839954,0.00126949,0.000105634,0.0006522323,0.002580555,0.000009033567,0.00006852159,0.00005597523,0.0112632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9817926,"threshold_uncertainty_score":0.999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02082203788520107,"score_gpt":0.2199622436323211,"score_spread":0.1991402057471201,"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."}}