{"id":"W2517439203","doi":"10.1086/686971","title":"The Effects of Platform Most-Favored-Nation Clauses on Competition and Entry","year":2016,"lang":"en","type":"article","venue":"The Journal of Law and Economics","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Competition (biology); Context (archaeology); Business; Skew; Commerce; Phenomenon; Industrial organization; Advertising; Economics; Telecommunications; Computer 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":[0.005711301,0.0003924166,0.0008164529,0.0007316714,0.002075191,0.004565433,0.001447073,0.002288391,0.02422959],"category_scores_gemma":[0.0445838,0.0003839135,0.0007912332,0.0008574063,0.004000136,0.003902339,0.002585102,0.00430212,0.0007767743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002326611,"about_ca_system_score_gemma":0.002786514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01228239,"about_ca_topic_score_gemma":0.01683194,"domain_scores_codex":[0.9950457,0.002181444,0.0002695104,0.0005189304,0.0009973246,0.0009871664],"domain_scores_gemma":[0.8783022,0.09606469,0.0165468,0.00283553,0.002048292,0.004202601],"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":[0.006989935,0.005836718,0.2098473,0.0007378538,0.0004203234,0.002850167,0.00485202,0.03768379,0.01325954,0.6387704,0.01057543,0.06817652],"study_design_scores_gemma":[0.002225157,0.004906982,0.409268,0.0005612456,0.001124848,0.001184159,0.01492211,0.07195264,0.008489942,0.4548226,0.03004305,0.0004991964],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9109126,0.000630622,0.003597388,0.001821666,0.00006166787,0.000124526,0.0002532034,0.00003763316,0.08256073],"genre_scores_gemma":[0.9974288,0.0001076701,0.0003346971,0.0002722947,0.0000245654,0.00002381469,0.00004822238,0.000007961889,0.001751873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02422959,"threshold_uncertainty_score":0.08105606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01126065174163287,"score_gpt":0.1771989928543317,"score_spread":0.1659383411126989,"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."}}