{"id":"W4296309039","doi":"10.5539/ijef.v14n10p56","title":"Reflections on Learning from Observational Data","year":2022,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Observational study; Causal inference; Variation (astronomy); Sociology; Observational learning; Causality (physics); Data science; Positive economics; Epistemology; Computer science; Econometrics; Psychology; Economics; Statistics; Mathematics; Mathematics education","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2383976,0.001419755,0.003394021,0.005925157,0.004458798,0.01741278,0.008223216,0.02042732,0.008871586],"category_scores_gemma":[0.4802611,0.001404434,0.002658666,0.004753487,0.08013564,0.06763715,0.012879,0.04765607,0.002062798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01147991,"about_ca_system_score_gemma":0.01168541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008342225,"about_ca_topic_score_gemma":0.006126468,"domain_scores_codex":[0.8289753,0.1360269,0.004831939,0.008981751,0.01879499,0.002389058],"domain_scores_gemma":[0.2166721,0.7425657,0.006875525,0.0141091,0.01699724,0.002780285],"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":[0.00007718702,0.00006263912,0.001394494,0.0008938928,0.0001293535,0.0001727456,0.006956047,0.001070972,0.00005135271,0.8856519,0.06828076,0.03525874],"study_design_scores_gemma":[0.00004833479,0.00002937007,0.0005136203,0.001690104,0.00001962418,0.00009768152,0.002242716,0.0009300729,0.000110893,0.8734199,0.1208411,0.00005666527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001442487,0.02270106,0.01447262,0.9464725,0.004052181,0.00004650175,0.000268951,0.00003511897,0.01050865],"genre_scores_gemma":[0.2120878,0.09581678,0.0531568,0.5556886,0.07075842,0.001180939,0.0005649404,0.0004006848,0.01034507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2383976,"threshold_uncertainty_score":0.9391913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2520178590750839,"score_gpt":0.4087191000723525,"score_spread":0.1567012409972686,"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."}}