{"id":"W2743507705","doi":"10.1007/s10961-017-9615-7","title":"Collaboration or funding: lessons from a study of nanotechnology patenting in Canada and the United States","year":2017,"lang":"en","type":"article","venue":"The Journal of Technology Transfer","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Productivity; Context (archaeology); Government (linguistics); Quality (philosophy); Position (finance); Technological change; Political science; Knowledge production; Business; Knowledge management; Economic growth; Economics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.006542671,0.0002561124,0.001077069,0.004103266,0.01574343,0.01092691,0.002756161,0.003855903,0.006968242],"category_scores_gemma":[0.03407764,0.0002610106,0.0005601174,0.01213459,0.009145354,0.006837888,0.004561651,0.004333207,0.0002354593],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06241781,"about_ca_system_score_gemma":0.1353605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9771325,"about_ca_topic_score_gemma":0.9877625,"domain_scores_codex":[0.9927443,0.001393215,0.0001861772,0.0004167873,0.00132645,0.003933149],"domain_scores_gemma":[0.9638385,0.02072285,0.003109236,0.0008906777,0.005381057,0.006057723],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005193187,0.0009791378,0.3668577,0.0003194317,0.0003459949,0.001595795,0.1246874,0.003522675,0.0005213289,0.3691099,0.02788805,0.1036534],"study_design_scores_gemma":[0.0002695725,0.000165458,0.439283,0.0008808369,0.0003524475,0.000315225,0.3858955,0.003270934,0.0007662254,0.06149896,0.1071475,0.0001543636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8722795,0.00459017,0.0009444708,0.03402627,0.00008372595,0.0001140269,0.0005347187,0.00002503604,0.08740214],"genre_scores_gemma":[0.9939691,0.0009410848,0.000183672,0.001243787,0.00002510509,0.00002276844,0.0001206584,0.00001198164,0.003481806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9934573,"threshold_uncertainty_score":0.452875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05596099088917644,"score_gpt":0.2682520752944919,"score_spread":0.2122910844053155,"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."}}