{"id":"W3123936072","doi":"","title":"Learning through Crowdfunding","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Stylized fact; Moral hazard; Transparency (behavior); Business; Investment (military); On demand; Raising (metalworking); Nothing; Microeconomics; Economics; Commerce; Computer science; Incentive; Computer security; Engineering; Political science","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":[0.003161675,0.0008455044,0.001263574,0.0007656807,0.0008697436,0.002176253,0.001652407,0.003155614,0.01251734],"category_scores_gemma":[0.0181524,0.0004237708,0.0008411158,0.0004798982,0.002421531,0.004062398,0.001776592,0.00197559,0.0008596969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001803461,"about_ca_system_score_gemma":0.001415528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004707463,"about_ca_topic_score_gemma":0.002512413,"domain_scores_codex":[0.9983146,0.0006615194,0.00004591595,0.0003720621,0.0002310695,0.0003747449],"domain_scores_gemma":[0.9891714,0.007320954,0.001596726,0.0006414578,0.0004869398,0.0007824993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005699217,0.0004222822,0.006140658,0.0002433585,0.00007239349,0.0009512292,0.0007610922,0.3366712,0.00188411,0.6022583,0.01061986,0.03940559],"study_design_scores_gemma":[0.0003356614,0.0002342309,0.001092357,0.00006777195,0.00005090471,0.0001963148,0.0001916213,0.6172032,0.0007082776,0.3704549,0.009404866,0.00006003077],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3903278,0.001198797,0.5034956,0.01696879,0.0003651305,0.0007288805,0.00164049,0.000690205,0.08458424],"genre_scores_gemma":[0.9668598,0.0002931591,0.01116781,0.0004665555,0.0001003729,0.0002813568,0.0001165608,0.00002696321,0.0206874],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01251734,"threshold_uncertainty_score":0.04187465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04297090784647255,"score_gpt":0.3017590826440946,"score_spread":0.2587881747976221,"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."}}