{"id":"W4408567212","doi":"10.1016/j.finr.2025.100006","title":"Supervised learning models, statistical models or hybrid models? A prediction of clean energy stock based on fear and fundamental factors","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Computer science; Statistical learning; Artificial intelligence; Machine learning; Stock (firearms); Predictive modelling; Statistical model; Engineering","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":[0.001098166,0.0004521641,0.0004908787,0.0003385022,0.0001084086,0.0007847833,0.0007054319,0.0005896928,0.001149899],"category_scores_gemma":[0.002393484,0.0002182606,0.0004527399,0.0003801126,0.0003289965,0.00124732,0.0002689545,0.0007937477,0.0002777035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003436787,"about_ca_system_score_gemma":0.0004453294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004334155,"about_ca_topic_score_gemma":0.005031282,"domain_scores_codex":[0.999804,0.00008786291,0.000009116605,0.00004595876,0.00003221783,0.00002099015],"domain_scores_gemma":[0.9992267,0.0004662449,0.0001109296,0.00007851498,0.00008593219,0.00003176073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008554527,0.00011827,0.008640933,0.00009630799,0.0001691096,0.000068093,0.00009419705,0.8776315,0.0007825422,0.03480959,0.003139517,0.07436442],"study_design_scores_gemma":[0.000004133809,0.00001598469,0.0006895487,0.00000867071,0.000007351651,0.00001009983,0.000009666882,0.9864284,0.0001024181,0.01233598,0.0003825164,0.000005260235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2251266,0.002159008,0.7585986,0.004045041,0.0002090965,0.00006690849,0.00056109,0.0007251563,0.008508399],"genre_scores_gemma":[0.9418628,0.0009047242,0.05229159,0.0002851389,0.0001806793,0.00007399268,0.0003107475,0.0000325941,0.004057797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004334155,"threshold_uncertainty_score":0.008617878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4432901866504693,"score_gpt":0.4878487706345707,"score_spread":0.04455858398410134,"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."}}