{"id":"W4367368846","doi":"10.1177/23409444231166717","title":"Understanding the effect of boundary spanning activities on team identification in new product development teams","year":2023,"lang":"en","type":"article","venue":"BRQ Business Research Quarterly","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Boundary spanning; Team composition; Team effectiveness; Identification (biology); New product development; Relevance (law); Affect (linguistics); Knowledge management; Business; Boundary (topology); Psychology; Product (mathematics); Marketing; Computer science; Mathematics; 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":[0.005600851,0.0002078292,0.0002307136,0.001383125,0.001276917,0.00260798,0.0006247816,0.0007474853,0.004221221],"category_scores_gemma":[0.04485049,0.0002334709,0.0001923566,0.0009433716,0.002091967,0.003085928,0.003613535,0.001179528,0.0003986856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161418,"about_ca_system_score_gemma":0.001424023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002455595,"about_ca_topic_score_gemma":0.002247697,"domain_scores_codex":[0.9955512,0.003111484,0.0001572223,0.0002682804,0.0005450586,0.0003667441],"domain_scores_gemma":[0.931596,0.04461568,0.01496573,0.001866418,0.002185933,0.004770259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005837316,0.001330791,0.7665574,0.0002604099,0.00009003201,0.0003806508,0.04228218,0.003262523,0.003646942,0.0271661,0.0009768731,0.1534624],"study_design_scores_gemma":[0.00002742052,0.0003007885,0.9472823,0.0001603676,0.0000370247,0.0001112831,0.02545231,0.003576949,0.0005214421,0.02072775,0.001778836,0.00002356137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885412,0.0002161022,0.001141555,0.0006371332,0.00000687523,0.00001338082,0.00001109653,0.000004749026,0.009427896],"genre_scores_gemma":[0.9993049,0.0001057944,0.0003448076,0.00003319436,0.000005644825,0.00001002228,0.000009694062,0.000001678675,0.0001843344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005600851,"threshold_uncertainty_score":0.02962053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236409838350812,"score_gpt":0.3998315380124728,"score_spread":0.2761905541773916,"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."}}