{"id":"W4283792026","doi":"10.1111/poms.13782","title":"Contingent stimulus in crowdfunding","year":2022,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Upgrade; Stimulus (psychology); Business; Nothing; Cascade; Marketing; Computer science; Economics; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006904829,0.001032283,0.001794068,0.00100505,0.001499962,0.002501556,0.001630313,0.002876762,0.01250703],"category_scores_gemma":[0.03262468,0.0007240128,0.0009737947,0.0009061508,0.002436278,0.003135895,0.00182863,0.002906432,0.001191166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002393919,"about_ca_system_score_gemma":0.001945922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005166302,"about_ca_topic_score_gemma":0.004396762,"domain_scores_codex":[0.9951913,0.002627942,0.0001689983,0.000971726,0.0003508355,0.000689169],"domain_scores_gemma":[0.9566621,0.03156903,0.006343207,0.002051212,0.001009065,0.002365472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002472417,0.001241424,0.0505076,0.0009722081,0.0002291388,0.001596809,0.002052236,0.5826769,0.00493157,0.2365175,0.01988207,0.09692013],"study_design_scores_gemma":[0.0005776455,0.0006640269,0.01804063,0.0001778492,0.0001264283,0.0002914034,0.001065749,0.7218412,0.002076167,0.2408939,0.01404003,0.0002049986],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7374338,0.00232226,0.2293172,0.00395819,0.0003123062,0.0008152676,0.002779804,0.001402343,0.02165876],"genre_scores_gemma":[0.9856973,0.0003368357,0.009704093,0.0002435381,0.00007857673,0.0002889997,0.0003510723,0.00006463693,0.00323492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01250703,"threshold_uncertainty_score":0.04184014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642979548711644,"score_gpt":0.2224822089794869,"score_spread":0.2060524134923705,"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."}}