{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00194659,0.000557858,0.0007261995,0.001027111,0.0004069517,0.001416892,0.001343655,0.0005849365,0.0002852502],"category_scores_gemma":[0.001900085,0.0005660118,0.0002865845,0.0003876177,0.0004445386,0.001615191,0.004379708,0.002610424,0.0005497488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001090627,"about_ca_system_score_gemma":0.000228019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002792376,"about_ca_topic_score_gemma":0.0001741856,"domain_scores_codex":[0.9956669,0.00005403043,0.0008583198,0.001478932,0.0004289032,0.001512919],"domain_scores_gemma":[0.9977987,0.0004271524,0.0005607046,0.000946872,0.0002293059,0.00003729465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003858683,0.0004082002,0.1593759,0.002970475,0.0003001793,0.0003749633,0.0004640992,0.006582335,0.001086266,0.146515,0.00316359,0.6783732],"study_design_scores_gemma":[0.001290835,0.00005893749,0.008471622,0.002894649,0.00002373082,0.00001175717,0.0008914136,0.008058612,0.0002594607,0.1216415,0.8544151,0.001982453],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2805398,0.00010284,0.00006727319,0.0007019285,0.001044058,0.0006270672,0.00001260109,0.0002458724,0.7166585],"genre_scores_gemma":[0.9821327,0.001188108,0.0002464919,0.0002606246,0.002054611,0.0002229318,0.00006425062,0.0002012616,0.013629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8512515,"threshold_uncertainty_score":0.9996906,"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."}}